diff --git a/docs/CTR/leaderboard/amazonelectronics_x1.csv b/docs/CTR/leaderboard/amazonelectronics_x1.csv
new file mode 100644
index 0000000..aa85e71
--- /dev/null
+++ b/docs/CTR/leaderboard/amazonelectronics_x1.csv
@@ -0,0 +1,13 @@
+Year,Publication,Model,Paper URL,gAUC,AUC,Logloss,Running Steps,Contributor
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.849405,0.848518,0.506075,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_amazonelectronics_x1,"Zhu et al."
+2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.852076,0.853685,0.479621,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_amazonelectronics_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.878957,0.881546,0.44011,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_amazonelectronics_x1,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.87889,0.881583,0.437653,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_amazonelectronics_x1,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.877829,0.880079,0.442113,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_amazonelectronics_x1,"Zhu et al."
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.879046,0.88116,0.444522,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_amazonelectronics_x1,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.878973,0.881289,0.438688,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_amazonelectronics_x1,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.878682,0.880402,0.444114,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1,"Zhu et al."
+2021,KDD'21,AOANet,https://dl.acm.org/doi/10.1145/3447548.3467133,0.879087,0.881228,0.439942,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AOANet/AOANet_amazonelectronics_x1,"Zhu et al."
+2018,KDD'18,DIN,https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction,0.883526,0.886028,0.43019,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN/DIN_amazonelectronics_x1,"Zhu et al."
+2019,AAAI'19,DIEN,https://arxiv.org/abs/1809.03672,0.885625,0.888777,0.425708,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN/DIEN_amazonelectronics_x1,"Zhu et al."
+2019,DLP-KDD'19,BST,https://arxiv.org/abs/1905.06874,0.884108,0.886424,0.430077,https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST/BST_amazonelectronics_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/amazonelectronics_x1.md b/docs/CTR/leaderboard/amazonelectronics_x1.md
index 17328b3..2b7a6d4 100644
--- a/docs/CTR/leaderboard/amazonelectronics_x1.md
+++ b/docs/CTR/leaderboard/amazonelectronics_x1.md
@@ -12,3 +12,17 @@ jupytext:
# AmazonElectronics_x1
+```{note}
+Please use the following evaluation settings for this benchmark:
++ Dataset split: [AmazonElectronics_x1](https://github.com/reczoo/Datasets/tree/main/Amazon/AmazonElectronics_x1)
++ Rare features filtering: min_categr_count=1
++ Embedding size: 64
+```
+
+🔥 **See the benchmarking results**:
+
+```{code-cell}
+from plots import show_table_gauc, show_plot_gauc
+show_plot_gauc("amazonelectronics_x1.csv")
+show_table_gauc("amazonelectronics_x1.csv")
+```
diff --git a/docs/CTR/leaderboard/avazu_x1.csv b/docs/CTR/leaderboard/avazu_x1.csv
index 1ef9988..0b224db 100644
--- a/docs/CTR/leaderboard/avazu_x1.csv
+++ b/docs/CTR/leaderboard/avazu_x1.csv
@@ -7,7 +7,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.7627,0.3677,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_avazu_x1,"Zhu et al."
2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.7602,0.3688,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_avazu_x1,"Zhu et al."
2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.7595,0.3689,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_avazu_x1,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.763,0.3682,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.763,0.3682,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x1,"Zhu et al."
2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.763,0.3676,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_avazu_x1,"Zhu et al."
2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.7649,0.3665,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_avazu_x1,"Zhu et al."
2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.7648,0.3667,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_avazu_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/avazu_x4_001.csv b/docs/CTR/leaderboard/avazu_x4_001.csv
index d50dfea..408376b 100644
--- a/docs/CTR/leaderboard/avazu_x4_001.csv
+++ b/docs/CTR/leaderboard/avazu_x4_001.csv
@@ -1,31 +1,31 @@
-Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
-2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7775,0.3815,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_avazu_x4_001,"Zhu et al."
-2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.7887,0.3754,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_avazu_x4_001,"Zhu et al."
-2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.7892,0.3745,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_avazu_x4_001,"Zhu et al."
-2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.7891,0.3754,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_avazu_x4_001,"Zhu et al."
-2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.7931,0.3720,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_avazu_x4_001,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.7928,0.3722,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x4_001,"Zhu et al."
-2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.7929,0.3720,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_avazu_x4_001,"Zhu et al."
-2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.7944,0.3712,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_avazu_x4_001,"Zhu et al."
-2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.7930,0.3721,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_avazu_x4_001,"Zhu et al."
-2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.7894,0.3743,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_avazu_x4_001,"Zhu et al."
-2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.7823,0.3793,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_avazu_x4_001,"Zhu et al."
-2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.7930,0.3719,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_avazu_x4_001,"Zhu et al."
-2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.7840,0.3779,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_avazu_x4_001,"Zhu et al."
-2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.7931,0.3719,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_avazu_x4_001,"Zhu et al."
-2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.7907,0.3744,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_avazu_x4_001,"Zhu et al."
-2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.7894,0.3742,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_avazu_x4_001,"Zhu et al."
-2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.7933,0.3718,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_avazu_x4_001,"Zhu et al."
-2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7879,0.3757,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_avazu_x4_001,"Zhu et al."
-2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7944,0.3714,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_avazu_x4_001,"Zhu et al."
-2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.7944,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_avazu_x4_001,"Zhu et al."
-2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.7891,0.3745,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_avazu_x4_001,"Zhu et al."
-2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.7902,0.3746,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_avazu_x4_001,"Zhu et al."
-2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.7915,0.3736,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_avazu_x4_001,"Zhu et al."
-2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.7992,0.3683,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_avazu_x4_001,"Zhu et al."
-2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.7953,0.3705,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_avazu_x4_001,"Zhu et al."
-2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.7885,0.3756,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_avazu_x4_001,"Zhu et al."
-2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7907,0.3740,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_avazu_x4_001,"Zhu et al."
-2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7929,0.3726,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_avazu_x4_001,"Zhu et al."
-2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.7882,0.3749,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_avazu_x4_001,"Zhu et al."
-2020,DLP-KDD'20,FLEN,https://arxiv.org/abs/1911.04690,0.7929,0.3720,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FLEN/FLEN_avazu_x4_001,"Zhu et al."
+Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
+2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7775,0.3815,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_avazu_x4_001,"Zhu et al."
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.7887,0.3754,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_avazu_x4_001,"Zhu et al."
+2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.7892,0.3745,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_avazu_x4_001,"Zhu et al."
+2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.7891,0.3754,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_avazu_x4_001,"Zhu et al."
+2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.7931,0.372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_avazu_x4_001,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.7928,0.3722,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x4_001,"Zhu et al."
+2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.7929,0.372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_avazu_x4_001,"Zhu et al."
+2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.7944,0.3712,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_avazu_x4_001,"Zhu et al."
+2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.793,0.3721,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_avazu_x4_001,"Zhu et al."
+2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.7894,0.3743,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_avazu_x4_001,"Zhu et al."
+2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.7823,0.3793,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_avazu_x4_001,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.793,0.3719,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_avazu_x4_001,"Zhu et al."
+2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.784,0.3779,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_avazu_x4_001,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.7931,0.3719,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_avazu_x4_001,"Zhu et al."
+2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.7907,0.3744,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_avazu_x4_001,"Zhu et al."
+2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.7894,0.3742,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_avazu_x4_001,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.7933,0.3718,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_avazu_x4_001,"Zhu et al."
+2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7879,0.3757,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_avazu_x4_001,"Zhu et al."
+2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7944,0.3714,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_avazu_x4_001,"Zhu et al."
+2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.7944,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_avazu_x4_001,"Zhu et al."
+2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.7891,0.3745,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_avazu_x4_001,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.7902,0.3746,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_avazu_x4_001,"Zhu et al."
+2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.7915,0.3736,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_avazu_x4_001,"Zhu et al."
+2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.7992,0.3683,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_avazu_x4_001,"Zhu et al."
+2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.7953,0.3705,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_avazu_x4_001,"Zhu et al."
+2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.7885,0.3756,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_avazu_x4_001,"Zhu et al."
+2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7907,0.374,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_avazu_x4_001,"Zhu et al."
+2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7929,0.3726,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_avazu_x4_001,"Zhu et al."
+2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.7882,0.3749,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_avazu_x4_001,"Zhu et al."
+2020,DLP-KDD'20,FLEN,https://arxiv.org/abs/1911.04690,0.7929,0.372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FLEN/FLEN_avazu_x4_001,"Zhu et al."
diff --git a/docs/CTR/leaderboard/avazu_x4_002.csv b/docs/CTR/leaderboard/avazu_x4_002.csv
index 80f0686..dea1b17 100644
--- a/docs/CTR/leaderboard/avazu_x4_002.csv
+++ b/docs/CTR/leaderboard/avazu_x4_002.csv
@@ -1,30 +1,30 @@
-Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
-2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7804,0.3799,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_avazu_x4_002,"Zhu et al."
-2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.7909,0.3736,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_avazu_x4_002,"Zhu et al."
-2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.7948,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_avazu_x4_002,"Zhu et al."
-2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.7925,0.3724,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_avazu_x4_002,"Zhu et al."
-2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.7840,0.3781,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_avazu_x4_002,"Zhu et al."
-2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.7914,0.3733,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_avazu_x4_002,"Zhu et al."
-2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.7940,0.3715,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_avazu_x4_002,"Zhu et al."
-2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.7932,0.3721,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_avazu_x4_002,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.7959,0.3705,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x4_002,"Zhu et al."
-2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.7957,0.3703,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_avazu_x4_002,"Zhu et al."
-2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.7962,0.3702,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_avazu_x4_002,"Zhu et al."
-2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.7962,0.3700,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_avazu_x4_002,"Zhu et al."
-2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.7840,0.3773,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_avazu_x4_002,"Zhu et al."
-2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.7965,0.3699,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_avazu_x4_002,"Zhu et al."
-2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.7929,0.3724,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_avazu_x4_002,"Zhu et al."
-2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.7967,0.3697,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_avazu_x4_002,"Zhu et al."
-2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.7922,0.3726,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_avazu_x4_002,"Zhu et al."
-2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.7953,0.3709,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_avazu_x4_002,"Zhu et al."
-2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.7944,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_avazu_x4_002,"Zhu et al."
-2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8003,0.3675,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_avazu_x4_002,"Zhu et al."
-2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.7971,0.3696,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_avazu_x4_002,"Zhu et al."
-2020,NeuralNetworks'20,ONN,https://arxiv.org/pdf/1904.12579,0.8001,0.3677,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_avazu_x4_002,"Zhu et al."
-2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.7927,0.3722,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_avazu_x4_002,"Zhu et al."
-2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7936,0.3720,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_avazu_x4_002,"Zhu et al."
-2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7965,0.3700,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_avazu_x4_002,"Zhu et al."
-2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.7912,0.3742,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_avazu_x4_002,"Zhu et al."
-2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7910,0.3735,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_avazu_x4_002,"Zhu et al."
-2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7992,0.3683,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_avazu_x4_002,"Zhu et al."
-2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.7988,0.3686,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_avazu_x4_002,"Zhu et al."
+Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
+2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7804,0.3799,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_avazu_x4_002,"Zhu et al."
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.7909,0.3736,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_avazu_x4_002,"Zhu et al."
+2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.7948,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_avazu_x4_002,"Zhu et al."
+2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.7925,0.3724,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_avazu_x4_002,"Zhu et al."
+2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.784,0.3781,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_avazu_x4_002,"Zhu et al."
+2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.7914,0.3733,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_avazu_x4_002,"Zhu et al."
+2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.794,0.3715,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_avazu_x4_002,"Zhu et al."
+2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.7932,0.3721,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_avazu_x4_002,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.7959,0.3705,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_avazu_x4_002,"Zhu et al."
+2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.7957,0.3703,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_avazu_x4_002,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.7962,0.3702,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_avazu_x4_002,"Zhu et al."
+2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.7962,0.37,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_avazu_x4_002,"Zhu et al."
+2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.784,0.3773,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_avazu_x4_002,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.7965,0.3699,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_avazu_x4_002,"Zhu et al."
+2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.7929,0.3724,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_avazu_x4_002,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.7967,0.3697,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_avazu_x4_002,"Zhu et al."
+2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.7922,0.3726,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_avazu_x4_002,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.7953,0.3709,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_avazu_x4_002,"Zhu et al."
+2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.7944,0.3711,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_avazu_x4_002,"Zhu et al."
+2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8003,0.3675,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_avazu_x4_002,"Zhu et al."
+2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.7971,0.3696,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_avazu_x4_002,"Zhu et al."
+2020,NeuralNetworks'20,ONN,https://arxiv.org/pdf/1904.12579,0.8001,0.3677,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_avazu_x4_002,"Zhu et al."
+2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.7927,0.3722,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_avazu_x4_002,"Zhu et al."
+2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7936,0.372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_avazu_x4_002,"Zhu et al."
+2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7965,0.37,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_avazu_x4_002,"Zhu et al."
+2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.7912,0.3742,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_avazu_x4_002,"Zhu et al."
+2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.791,0.3735,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_avazu_x4_002,"Zhu et al."
+2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.7992,0.3683,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_avazu_x4_002,"Zhu et al."
+2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.7988,0.3686,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_avazu_x4_002,"Zhu et al."
diff --git a/docs/CTR/leaderboard/criteo_x1.csv b/docs/CTR/leaderboard/criteo_x1.csv
index 96c8c7c..9fe7876 100644
--- a/docs/CTR/leaderboard/criteo_x1.csv
+++ b/docs/CTR/leaderboard/criteo_x1.csv
@@ -7,7 +7,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8053,0.4459,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_criteo_x1,"Zhu et al."
2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8063,0.4454,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_criteo_x1,"Zhu et al."
2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.8056,0.4463,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_criteo_x1,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.8137,0.4382,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.8137,0.4382,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x1,"Zhu et al."
2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8137,0.4383,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_criteo_x1,"Zhu et al."
2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8139,0.438,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_criteo_x1,"Zhu et al."
2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8137,0.4381,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_criteo_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/criteo_x4_001.csv b/docs/CTR/leaderboard/criteo_x4_001.csv
index 3c4c65b..1bcb2b5 100644
--- a/docs/CTR/leaderboard/criteo_x4_001.csv
+++ b/docs/CTR/leaderboard/criteo_x4_001.csv
@@ -1,30 +1,30 @@
-Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
-2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7934,0.4568,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_criteo_x4_001,"Zhu et al."
-2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8086,0.4431,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_criteo_x4_001,"Zhu et al."
-2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.8104,0.4415,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_criteo_x4_001,"Zhu et al."
-2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8107,0.4411,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_criteo_x4_001,"Zhu et al."
-2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8113,0.4407,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_criteo_x4_001,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.8140,0.4380,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x4_001,"Zhu et al."
-2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8142,0.4377,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_criteo_x4_001,"Zhu et al."
-2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8142,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_criteo_x4_001,"Zhu et al."
-2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8135,0.4384,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_criteo_x4_001,"Zhu et al."
-2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8093,0.4424,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_criteo_x4_001,"Zhu et al."
-2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.8060,0.4455,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_criteo_x4_001,"Zhu et al."
-2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8143,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_criteo_x4_001,"Zhu et al."
-2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.8060,0.4456,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_criteo_x4_001,"Zhu et al."
-2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8144,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_criteo_x4_001,"Zhu et al."
-2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8112,0.4408,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_criteo_x4_001,"Zhu et al."
-2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8127,0.4394,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_criteo_x4_001,"Zhu et al."
-2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8143,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_criteo_x4_001,"Zhu et al."
-2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8095,0.4424,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_criteo_x4_001,"Zhu et al."
-2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8127,0.4392,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_criteo_x4_001,"Zhu et al."
-2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8121,0.4398,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_criteo_x4_001,"Zhu et al."
-2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8119,0.4399,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_criteo_x4_001,"Zhu et al."
-2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8132,0.4390,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_criteo_x4_001,"Zhu et al."
-2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8138,0.4383,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_criteo_x4_001,"Zhu et al."
-2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8148,0.4372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_criteo_x4_001,"Zhu et al."
-2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8131,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_criteo_x4_001,"Zhu et al."
-2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8083,0.4434,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_criteo_x4_001,"Zhu et al."
-2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8115,0.4402,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_criteo_x4_001,"Zhu et al."
-2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8138,0.4384,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_criteo_x4_001,"Zhu et al."
-2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8104,0.4414,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_criteo_x4_001,"Zhu et al."
+Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
+2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7934,0.4568,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_criteo_x4_001,"Zhu et al."
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8086,0.4431,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_criteo_x4_001,"Zhu et al."
+2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.8104,0.4415,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_criteo_x4_001,"Zhu et al."
+2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8107,0.4411,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_criteo_x4_001,"Zhu et al."
+2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8113,0.4407,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_criteo_x4_001,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.814,0.438,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x4_001,"Zhu et al."
+2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8142,0.4377,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_criteo_x4_001,"Zhu et al."
+2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8142,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_criteo_x4_001,"Zhu et al."
+2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8135,0.4384,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_criteo_x4_001,"Zhu et al."
+2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8093,0.4424,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_criteo_x4_001,"Zhu et al."
+2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.806,0.4455,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_criteo_x4_001,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8143,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_criteo_x4_001,"Zhu et al."
+2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.806,0.4456,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_criteo_x4_001,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8144,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_criteo_x4_001,"Zhu et al."
+2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8112,0.4408,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_criteo_x4_001,"Zhu et al."
+2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8127,0.4394,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_criteo_x4_001,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8143,0.4376,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_criteo_x4_001,"Zhu et al."
+2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8095,0.4424,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_criteo_x4_001,"Zhu et al."
+2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8127,0.4392,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_criteo_x4_001,"Zhu et al."
+2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8121,0.4398,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_criteo_x4_001,"Zhu et al."
+2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8119,0.4399,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_criteo_x4_001,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8132,0.439,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_criteo_x4_001,"Zhu et al."
+2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8138,0.4383,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_criteo_x4_001,"Zhu et al."
+2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8148,0.4372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_criteo_x4_001,"Zhu et al."
+2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8131,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_criteo_x4_001,"Zhu et al."
+2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8083,0.4434,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_criteo_x4_001,"Zhu et al."
+2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8115,0.4402,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_criteo_x4_001,"Zhu et al."
+2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8138,0.4384,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_criteo_x4_001,"Zhu et al."
+2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8104,0.4414,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_criteo_x4_001,"Zhu et al."
diff --git a/docs/CTR/leaderboard/criteo_x4_002.csv b/docs/CTR/leaderboard/criteo_x4_002.csv
index 3ca520a..984fb64 100644
--- a/docs/CTR/leaderboard/criteo_x4_002.csv
+++ b/docs/CTR/leaderboard/criteo_x4_002.csv
@@ -1,30 +1,30 @@
-Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
-2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7936,0.4566,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_criteo_x4_002,"Zhu et al."
-2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8078,0.4445,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_criteo_x4_002,"Zhu et al."
-2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8098,0.4419,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_criteo_x4_002,"Zhu et al."
-2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8111,0.4409,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_criteo_x4_002,"Zhu et al."
-2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.8073,0.4443,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_criteo_x4_002,"Zhu et al."
-2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8115,0.4404,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_criteo_x4_002,"Zhu et al."
-2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8072,0.4443,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_criteo_x4_002,"Zhu et al."
-2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.8077,0.4440,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_criteo_x4_002,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.8112,0.4407,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x4_002,"Zhu et al."
-2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8129,0.4389,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_criteo_x4_002,"Zhu et al."
-2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8141,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_criteo_x4_002,"Zhu et al."
-2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8132,0.4388,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_criteo_x4_002,"Zhu et al."
-2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8139,0.4380,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_criteo_x4_002,"Zhu et al."
-2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.8047,0.4468,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_criteo_x4_002,"Zhu et al."
-2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8141,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_criteo_x4_002,"Zhu et al."
-2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8133,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_criteo_x4_002,"Zhu et al."
-2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8144,0.4375,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_criteo_x4_002,"Zhu et al."
-2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8129,0.4390,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_criteo_x4_002,"Zhu et al."
-2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8134,0.4385,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_criteo_x4_002,"Zhu et al."
-2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8141,0.4379,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_criteo_x4_002,"Zhu et al."
-2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8134,0.4386,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_criteo_x4_002,"Zhu et al."
-2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8141,0.4381,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_criteo_x4_002,"Zhu et al."
-2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8142,0.4381,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_criteo_x4_002,"Zhu et al."
-2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8117,0.4401,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_criteo_x4_002,"Zhu et al."
-2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8097,0.4418,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_criteo_x4_002,"Zhu et al."
-2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8134,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_criteo_x4_002,"Zhu et al."
-2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8105,0.4413,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_criteo_x4_002,"Zhu et al."
-2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8110,0.4410,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_criteo_x4_002,"Zhu et al."
-2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8127,0.4391,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_criteo_x4_002,"Zhu et al."
+Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
+2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7936,0.4566,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_criteo_x4_002,"Zhu et al."
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8078,0.4445,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_criteo_x4_002,"Zhu et al."
+2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8098,0.4419,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_criteo_x4_002,"Zhu et al."
+2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8111,0.4409,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_criteo_x4_002,"Zhu et al."
+2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.8073,0.4443,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_criteo_x4_002,"Zhu et al."
+2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8115,0.4404,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_criteo_x4_002,"Zhu et al."
+2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8072,0.4443,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_criteo_x4_002,"Zhu et al."
+2015,CIKM'15,CCPM,http://www.escience.cn/system/download/73676,0.8077,0.444,https://github.com/reczoo/BARS/tree/main/ranking/ctr/CCPM/CCPM_criteo_x4_002,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.8112,0.4407,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_criteo_x4_002,"Zhu et al."
+2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8129,0.4389,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_criteo_x4_002,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8141,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_criteo_x4_002,"Zhu et al."
+2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8132,0.4388,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_criteo_x4_002,"Zhu et al."
+2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8139,0.438,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_criteo_x4_002,"Zhu et al."
+2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.8047,0.4468,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_criteo_x4_002,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8141,0.4378,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_criteo_x4_002,"Zhu et al."
+2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8133,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_criteo_x4_002,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8144,0.4375,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_criteo_x4_002,"Zhu et al."
+2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8129,0.439,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_criteo_x4_002,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8134,0.4385,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_criteo_x4_002,"Zhu et al."
+2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8141,0.4379,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_criteo_x4_002,"Zhu et al."
+2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8134,0.4386,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_criteo_x4_002,"Zhu et al."
+2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8141,0.4381,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_criteo_x4_002,"Zhu et al."
+2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8142,0.4381,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_criteo_x4_002,"Zhu et al."
+2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8117,0.4401,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_criteo_x4_002,"Zhu et al."
+2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8097,0.4418,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_criteo_x4_002,"Zhu et al."
+2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8134,0.4387,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_criteo_x4_002,"Zhu et al."
+2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8105,0.4413,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_criteo_x4_002,"Zhu et al."
+2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.811,0.441,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_criteo_x4_002,"Zhu et al."
+2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8127,0.4391,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_criteo_x4_002,"Zhu et al."
diff --git a/docs/CTR/leaderboard/frappe_x1.csv b/docs/CTR/leaderboard/frappe_x1.csv
index 8a47f71..9939597 100644
--- a/docs/CTR/leaderboard/frappe_x1.csv
+++ b/docs/CTR/leaderboard/frappe_x1.csv
@@ -7,7 +7,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.9804,0.2058,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_frappe_x1,"Zhu et al."
2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.9776,0.203,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_frappe_x1,"Zhu et al."
2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.9749,0.2004,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_frappe_x1,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.9833,0.1622,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_frappe_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.9833,0.1622,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_frappe_x1,"Zhu et al."
2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.9841,0.154,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_frappe_x1,"Zhu et al."
2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.9841,0.149,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_frappe_x1,"Zhu et al."
2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.9842,0.1482,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_frappe_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/kkbox_x1.csv b/docs/CTR/leaderboard/kkbox_x1.csv
index e99e13d..6bf45e8 100644
--- a/docs/CTR/leaderboard/kkbox_x1.csv
+++ b/docs/CTR/leaderboard/kkbox_x1.csv
@@ -1,29 +1,29 @@
-Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
-2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7678,0.5746,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_kkbox_x1,"Zhu et al."
-2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8304,0.5060,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_kkbox_x1,"Zhu et al."
-2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8376,0.4974,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_kkbox_x1,"Zhu et al."
-2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8406,0.4971,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_kkbox_x1,"Zhu et al."
-2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.8175,0.5241,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_kkbox_x1,"Zhu et al."
-2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8315,0.5048,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_kkbox_x1,"Zhu et al."
-2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8285,0.5102,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_kkbox_x1,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.8501,0.4811,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_kkbox_x1,"Zhu et al."
-2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8504,0.4852,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_kkbox_x1,"Zhu et al."
-2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8531,0.4785,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_kkbox_x1,"Zhu et al."
-2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8515,0.4793,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_kkbox_x1,"Zhu et al."
-2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8495,0.4799,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_kkbox_x1,"Zhu et al."
-2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.8116,0.5283,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_kkbox_x1,"Zhu et al."
-2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8531,0.4766,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_kkbox_x1,"Zhu et al."
-2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8427,0.4908,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_kkbox_x1,"Zhu et al."
-2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8535,0.4772,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_kkbox_x1,"Zhu et al."
-2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8436,0.4919,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_kkbox_x1,"Zhu et al."
-2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8534,0.4773,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_kkbox_x1,"Zhu et al."
-2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8472,0.4896,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_kkbox_x1,"Zhu et al."
-2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8499,0.4814,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_kkbox_x1,"Zhu et al."
-2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8522,0.4801,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_kkbox_x1,"Zhu et al."
-2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8498,0.4856,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_kkbox_x1,"Zhu et al."
-2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8426,0.4910,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_kkbox_x1,"Zhu et al."
-2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8489,0.4842,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_kkbox_x1,"Zhu et al."
-2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8202,0.5188,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_kkbox_x1,"Zhu et al."
-2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8392,0.4970,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_kkbox_x1,"Zhu et al."
-2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8521,0.4781,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_kkbox_x1,"Zhu et al."
-2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8459,0.4863,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_kkbox_x1,"Zhu et al."
+Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
+2007,WWW'07,LR,https://dl.acm.org/citation.cfm?id=1242643,0.7678,0.5746,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LR/LR_kkbox_x1,"Zhu et al."
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.8304,0.506,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_kkbox_x1,"Zhu et al."
+2016,RecSys'16,FFM,https://dl.acm.org/citation.cfm?id=2959134,0.8376,0.4974,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FFM/FFM_kkbox_x1,"Zhu et al."
+2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.8406,0.4971,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_kkbox_x1,"Zhu et al."
+2017,IJCAI'17,AFM,http://www.ijcai.org/proceedings/2017/0435.pdf,0.8175,0.5241,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFM/AFM_kkbox_x1,"Zhu et al."
+2016,NIPS'16,HOFM,https://papers.nips.cc/paper/6144-higher-order-factorization-machines.pdf,0.8315,0.5048,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HOFM/HOFM_kkbox_x1,"Zhu et al."
+2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.8285,0.5102,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_kkbox_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.8501,0.4811,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_kkbox_x1,"Zhu et al."
+2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.8504,0.4852,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_kkbox_x1,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.8531,0.4785,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_kkbox_x1,"Zhu et al."
+2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.8515,0.4793,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_kkbox_x1,"Zhu et al."
+2016,KDD'16,DeepCrossing,https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf,0.8495,0.4799,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepCrossing/DeepCross_kkbox_x1,"Zhu et al."
+2017,ADKDD'17,CrossNet,https://arxiv.org/abs/1708.05123,0.8116,0.5283,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/CrossNet_kkbox_x1,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.8531,0.4766,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_kkbox_x1,"Zhu et al."
+2018,KDD'18,CIN,https://arxiv.org/pdf/1803.05170.pdf,0.8427,0.4908,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/CIN_kkbox_x1,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.8535,0.4772,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_kkbox_x1,"Zhu et al."
+2019,CIKM'19,AutoInt,https://arxiv.org/abs/1810.11921,0.8436,0.4919,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_kkbox_x1,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.8534,0.4773,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt+_kkbox_x1,"Zhu et al."
+2019,CIKM'19,FiGNN,https://arxiv.org/abs/1910.05552,0.8472,0.4896,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiGNN/FiGNN_kkbox_x1,"Zhu et al."
+2019,RecSys'19,FiBiNET,https://arxiv.org/abs/1905.09433,0.8499,0.4814,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FiBiNET/FiBiNET_kkbox_x1,"Zhu et al."
+2019,WWW'19,FGCNN,https://arxiv.org/abs/1904.04447,0.8522,0.4801,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FGCNN/FGCNN_kkbox_x1,"Zhu et al."
+2020,NeuralNets'20,ONN,https://arxiv.org/pdf/1904.12579,0.8498,0.4856,https://github.com/reczoo/BARS/tree/main/ranking/ctr/ONN/ONN_kkbox_x1,"Zhu et al."
+2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8426,0.491,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_kkbox_x1,"Zhu et al."
+2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8489,0.4842,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_kkbox_x1,"Zhu et al."
+2020,AAAI'20,LorentzFM,https://arxiv.org/abs/1911.09821,0.8202,0.5188,https://github.com/reczoo/BARS/tree/main/ranking/ctr/LorentzFM/LorentzFM_kkbox_x1,"Zhu et al."
+2019,AAAI'19,HFM,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8392,0.497,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM_kkbox_x1,"Zhu et al."
+2019,AAAI'19,HFM+,https://ojs.aaai.org//index.php/AAAI/article/view/4448,0.8521,0.4781,https://github.com/reczoo/BARS/tree/main/ranking/ctr/HFM/HFM+_kkbox_x1,"Zhu et al."
+2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8459,0.4863,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_kkbox_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/kuaivideo_x1.csv b/docs/CTR/leaderboard/kuaivideo_x1.csv
new file mode 100644
index 0000000..2ad53cd
--- /dev/null
+++ b/docs/CTR/leaderboard/kuaivideo_x1.csv
@@ -0,0 +1,13 @@
+Year,Publication,Model,Paper URL,gAUC,AUC,Logloss,Running Steps,Contributor
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.659864,0.74179,0.439771,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_kuaivideo_x1,"Zhu et al."
+2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.65522,0.738873,0.442923,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_kuaivideo_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.665842,0.745264,0.440147,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_kuaivideo_x1,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.666502,0.745152,0.440012,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_kuaivideo_x1,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.665813,0.74608,0.440783,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_kuaivideo_x1,"Zhu et al."
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.667472,0.746953,0.437494,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_kuaivideo_x1,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.669617,0.747075,0.437683,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_kuaivideo_x1,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.666719,0.746899,0.435692,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1,"Zhu et al."
+2021,KDD'21,AOANet,https://dl.acm.org/doi/10.1145/3447548.3467133,0.667875,0.74702,0.438034,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AOANet/AOANet_kuaivideo_x1,"Zhu et al."
+2018,KDD'18,DIN,https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction,0.669568,0.749537,0.43212,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN/DIN_kuaivideo_x1,"Zhu et al."
+2019,AAAI'19,DIEN,https://arxiv.org/abs/1809.03672,0.671148,0.750372,0.433049,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN/DIEN_kuaivideo_x1,"Zhu et al."
+2019,DLP-KDD'19,BST,https://arxiv.org/abs/1905.06874,0.669039,0.748407,0.433819,https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST/BST_kuaivideo_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/kuaivideo_x1.md b/docs/CTR/leaderboard/kuaivideo_x1.md
index 1bb80dd..235fd95 100644
--- a/docs/CTR/leaderboard/kuaivideo_x1.md
+++ b/docs/CTR/leaderboard/kuaivideo_x1.md
@@ -10,4 +10,19 @@ jupytext:
jupytext_version: 1.14.5
---
-# KuaiVideo_x1
\ No newline at end of file
+# KuaiVideo_x1
+
+```{note}
+Please use the following evaluation settings for this benchmark:
++ Dataset split: [KuaiVideo_x1](https://github.com/reczoo/Datasets/tree/main/KuaiShou/KuaiVideo_x1)
++ Rare features filtering: min_categr_count=10
++ Embedding size: 64
+```
+
+🔥 **See the benchmarking results**:
+
+```{code-cell}
+from plots import show_table_gauc, show_plot_gauc
+show_plot_gauc("kuaivideo_x1.csv")
+show_table_gauc("kuaivideo_x1.csv")
+```
diff --git a/docs/CTR/leaderboard/microvideo1.7m_x1.csv b/docs/CTR/leaderboard/microvideo1.7m_x1.csv
new file mode 100644
index 0000000..33c71b5
--- /dev/null
+++ b/docs/CTR/leaderboard/microvideo1.7m_x1.csv
@@ -0,0 +1,13 @@
+Year,Publication,Model,Paper URL,gAUC,AUC,Logloss,Running Steps,Contributor
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.672374,0.718639,0.415241,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_microvideo1.7m_x1,"Zhu et al."
+2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.673692,0.721519,0.418067,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_microvideo1.7m_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.685716,0.734555,0.411947,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_microvideo1.7m_x1,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.685246,0.73367,0.413181,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_microvideo1.7m_x1,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.685458,0.734198,0.413294,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_microvideo1.7m_x1,"Zhu et al."
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.685946,0.734367,0.412206,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_microvideo1.7m_x1,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.688869,0.736228,0.412212,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_microvideo1.7m_x1,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.684609,0.733822,0.413313,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1,"Zhu et al."
+2021,KDD'21,AOANet,https://dl.acm.org/doi/10.1145/3447548.3467133,0.685797,0.734644,0.412282,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AOANet/AOANet_microvideo1.7m_x1,"Zhu et al."
+2018,KDD'18,DIN,https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction,0.688282,0.736006,0.411558,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN/DIN_microvideo1.7m_x1,"Zhu et al."
+2019,AAAI'19,DIEN,https://arxiv.org/abs/1809.03672,0.68672,0.732075,0.412213,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN/DIEN_microvideo1.7m_x1,"Zhu et al."
+2019,DLP-KDD'19,BST,https://arxiv.org/abs/1905.06874,0.685436,0.73415,0.411837,https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST/BST_microvideo1.7m_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/microvideo1.7m_x1.md b/docs/CTR/leaderboard/microvideo1.7m_x1.md
index 73481af..e5ce6c3 100644
--- a/docs/CTR/leaderboard/microvideo1.7m_x1.md
+++ b/docs/CTR/leaderboard/microvideo1.7m_x1.md
@@ -10,4 +10,19 @@ jupytext:
jupytext_version: 1.14.5
---
-# MicroVideo1.7M_x1
\ No newline at end of file
+# MicroVideo1.7M_x1
+
+```{note}
+Please use the following evaluation settings for this benchmark:
++ Dataset split: [MicroVideo1.7M_x1](https://github.com/reczoo/Datasets/tree/main/MicroVideo1.7M/MicroVideo1.7M_x1)
++ Rare features filtering: min_categr_count=1
++ Embedding size: 64
+```
+
+🔥 **See the benchmarking results**:
+
+```{code-cell}
+from plots import show_table_gauc, show_plot_gauc
+show_plot_gauc("microvideo1.7m_x1.csv")
+show_table_gauc("microvideo1.7m_x1.csv")
+```
diff --git a/docs/CTR/leaderboard/movielenslatest_x1.csv b/docs/CTR/leaderboard/movielenslatest_x1.csv
index c9bc468..bffac27 100644
--- a/docs/CTR/leaderboard/movielenslatest_x1.csv
+++ b/docs/CTR/leaderboard/movielenslatest_x1.csv
@@ -7,7 +7,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
2017,SIGIR'17,NFM,https://dl.acm.org/citation.cfm?id=3080777,0.9496,0.2664,https://github.com/reczoo/BARS/tree/main/ranking/ctr/NFM/NFM_movielenslatest_x1,"Zhu et al."
2018,WWW'18,FwFM,https://arxiv.org/pdf/1806.03514.pdf,0.9558,0.2426,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FwFM/FwFM_movielenslatest_x1,"Zhu et al."
2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.9465,0.2714,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_movielenslatest_x1,"Zhu et al."
-2016,RecSys'16,YoutubeDNN,http://art.yale.edu/file_columns/0001/1132/covington.pdf,0.9678,0.2388,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_movielenslatest_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.9678,0.2388,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_movielenslatest_x1,"Zhu et al."
2016,ICDM'16,IPNN,https://arxiv.org/pdf/1611.00144.pdf,0.9699,0.2095,https://github.com/reczoo/BARS/tree/main/ranking/ctr/PNN/IPNN_movielenslatest_x1,"Zhu et al."
2016,DLRS'16,Wide&Deep,https://arxiv.org/pdf/1606.07792.pdf,0.9688,0.2161,https://github.com/reczoo/BARS/tree/main/ranking/ctr/WideDeep/WideDeep_movielenslatest_x1,"Zhu et al."
2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.9685,0.213,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_movielenslatest_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/plots.py b/docs/CTR/leaderboard/plots.py
index 9e28339..98d43fc 100644
--- a/docs/CTR/leaderboard/plots.py
+++ b/docs/CTR/leaderboard/plots.py
@@ -5,6 +5,7 @@
import itables.options as opt
opt.columnDefs = [{"className": "dt-center", "targets": "_all"}]
+
def show_table(csv_path):
df = pd.read_csv(csv_path)
df["Model"] = df.apply(lambda x: f"{x['Model']}", axis=1)
@@ -52,3 +53,56 @@ def show_plot(csv_path):
title_text="Logloss"
)
fig.show()
+
+def show_table_gauc(csv_path):
+ df = pd.read_csv(csv_path)
+ df["Model"] = df.apply(lambda x: f"{x['Model']}", axis=1)
+ del df["Paper URL"]
+ df["Running Steps"] = df["Running Steps"].map(lambda x: f"🔗")
+ df = df.sort_values(by=["gAUC"], ascending=False).reset_index(drop=True)
+ df.insert(0, "Rank", range(1, len(df) + 1))
+ df[['gAUC', 'AUC', 'Logloss']] = df[['gAUC', 'AUC', 'Logloss']].applymap('{:.4f}'.format)
+ show(df, lengthMenu=[10, 20, 50, 100], classes="display")
+
+def show_plot_gauc(csv_path):
+ df = pd.read_csv(csv_path).sort_values(by="gAUC", ascending=True)
+ fig = make_subplots(specs=[[{"secondary_y": True}]])
+ fig.add_trace(
+ go.Scatter(x=df["Model"], y=df["gAUC"], name="gAUC", mode='lines+markers',
+ line=dict(color="#3e8c58", shape="spline", smoothing=1.3), marker=dict(size=7)),
+ secondary_y=False,
+ )
+ fig.add_trace(
+ go.Scatter(x=df["Model"], y=df["AUC"], name="AUC", mode='lines+markers',
+ line=dict(color="#0071a7", shape="spline", smoothing=1.3), marker=dict(size=7)),
+ secondary_y=False,
+ )
+ fig.add_trace(
+ go.Scatter(x=df["Model"], y=df["Logloss"], name="Logloss", mode='lines+markers',
+ line=dict(color="#ff404e", shape="spline", smoothing=1.3), marker=dict(size=7)),
+ secondary_y=True,
+ )
+
+ fig.update_layout(
+ title="Sorted benchmarking results by gAUC",
+ title_x=0.5,
+ plot_bgcolor='white',
+ autosize=True,
+ width=890,
+ height=450,
+ legend=dict(orientation="h", x=0.4, y=-0.4)
+ )
+ fig.update_xaxes(showgrid=False)
+ fig.update_yaxes(
+ showgrid=True,
+ gridcolor='lightgrey',
+ secondary_y=False,
+ title_text="gAUC/AUC"
+ )
+ fig.update_yaxes(
+ showgrid=False,
+ gridcolor='lightgrey',
+ secondary_y=True,
+ title_text="Logloss"
+ )
+ fig.show()
diff --git a/docs/CTR/leaderboard/taobaoad_x1.csv b/docs/CTR/leaderboard/taobaoad_x1.csv
new file mode 100644
index 0000000..f5d275c
--- /dev/null
+++ b/docs/CTR/leaderboard/taobaoad_x1.csv
@@ -0,0 +1,13 @@
+Year,Publication,Model,Paper URL,gAUC,AUC,Logloss,Running Steps,Contributor
+2010,ICDM'10,FM,https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf,0.563808,0.623407,0.196925,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FM/FM_taobaoad_x1,"Zhu et al."
+2021,WWW'21,FmFM,https://arxiv.org/abs/2102.12994,0.571647,0.633517,0.196312,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FmFM/FmFM_taobaoad_x1,"Zhu et al."
+2016,RecSys'16,YoutubeDNN,https://research.google.com/pubs/archive/45530.pdf,0.573269,0.646715,0.193133,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DNN/DNN_taobaoad_x1,"Zhu et al."
+2017,IJCAI'17,DeepFM,https://arxiv.org/abs/1703.04247,0.569739,0.636426,0.196501,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DeepFM/DeepFM_taobaoad_x1,"Zhu et al."
+2017,ADKDD'17,DCN,https://arxiv.org/abs/1708.05123,0.573908,0.648805,0.19304,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCN/DCN_taobaoad_x1,"Zhu et al."
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.574892,0.649458,0.192927,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_taobaoad_x1,"Zhu et al."
+2018,KDD'18,xDeepFM,https://arxiv.org/pdf/1803.05170.pdf,0.572884,0.639251,0.195328,https://github.com/reczoo/BARS/tree/main/ranking/ctr/xDeepFM/xDeepFM_taobaoad_x1,"Zhu et al."
+2019,CIKM'19,AutoInt+,https://arxiv.org/abs/1810.11921,0.574437,0.648629,0.19302,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AutoInt/AutoInt_taobaoad_x1,"Zhu et al."
+2021,KDD'21,AOANet,https://dl.acm.org/doi/10.1145/3447548.3467133,0.573251,0.650041,0.192513,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AOANet/AOANet_taobaoad_x1,"Zhu et al."
+2018,KDD'18,DIN,https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction,0.576459,0.652399,0.192445,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN/DIN_taobaoad_x1,"Zhu et al."
+2019,AAAI'19,DIEN,https://arxiv.org/abs/1809.03672,0.576916,0.652937,0.19284,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN/DIEN_taobaoad_x1,"Zhu et al."
+2019,DLP-KDD'19,BST,https://arxiv.org/abs/1905.06874,0.576304,0.651131,0.192842,https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST/BST_taobaoad_x1,"Zhu et al."
diff --git a/docs/CTR/leaderboard/taobaoad_x1.md b/docs/CTR/leaderboard/taobaoad_x1.md
index 7b58f0f..5d08441 100644
--- a/docs/CTR/leaderboard/taobaoad_x1.md
+++ b/docs/CTR/leaderboard/taobaoad_x1.md
@@ -10,4 +10,19 @@ jupytext:
jupytext_version: 1.14.5
---
-# TaobaoAd_x1
\ No newline at end of file
+# TaobaoAd_x1
+
+```{note}
+Please use the following evaluation settings for this benchmark:
++ Dataset split: [TaobaoAd_x1](https://github.com/reczoo/Datasets/tree/main/Taobao/TaobaoAd_x1)
++ Rare features filtering: min_categr_count=10
++ Embedding size: 32
+```
+
+🔥 **See the benchmarking results**:
+
+```{code-cell}
+from plots import show_table_gauc, show_plot_gauc
+show_plot_gauc("taobaoad_x1.csv")
+show_table_gauc("taobaoad_x1.csv")
+```
diff --git a/docs/CTR/papers.md b/docs/CTR/papers.md
index a293cc1..0aa5ffa 100644
--- a/docs/CTR/papers.md
+++ b/docs/CTR/papers.md
@@ -8,11 +8,11 @@ A curated list of CTR prediction models
| | | | | |
| :---------:|:------:|:------:|:------:|:------:|
| **2023** | [FinalNet](https://dl.acm.org/doi/10.1145/3539618.3591988) {cite}`FinalNet`
SIGIR'23
Huawei | [FinalMLP](https://arxiv.org/abs/2304.00902) {cite}`FinalMLP`
AAAI'23
Huawei | [EulerNet](https://arxiv.org/abs/2304.10711) {cite}`EulerNet`
SIGIR'23
Huawei | [GDCN](https://arxiv.org/abs/2311.04635) {cite}`GDCN`
CIKM'23
Microsoft |
-| | [MemoNet](https://arxiv.org/abs/2211.01334) {cite}`MemoNet`
CIKM'23
Sina Weibo |
-| **2022** | [FRNet](https://arxiv.org/abs/2204.08758) {cite}`FRNet`
SIGIR'22
Microsoft | [APG](https://arxiv.org/abs/2203.16218) {cite}`APG`
NeurIPS'22
Alibaba | [FINT](https://arxiv.org/abs/2107.01999) {cite}`FINT`
ICASSP'22
iQIYI |
+| | [MemoNet](https://arxiv.org/abs/2211.01334) {cite}`MemoNet`
CIKM'23
Sina Weibo | [AdaEnsemble](https://arxiv.org/abs/2301.08353) {cite}`AdaEnsemble`
AdKDD'23
Credit Karma |
+| **2022** | [FRNet](https://arxiv.org/abs/2204.08758) {cite}`FRNet`
SIGIR'22
Microsoft | [APG](https://arxiv.org/abs/2203.16218) {cite}`APG`
NeurIPS'22
Alibaba | [FINT](https://arxiv.org/abs/2107.01999) {cite}`FINT`
ICASSP'22
iQIYI | [DHEN](https://arxiv.org/abs/2203.11014) {cite}`DHEN`
DLP-KDD'22
Meta |
| **2021** | [DCN-V2](https://arxiv.org/abs/2008.13535) {cite}`DCNv2`
WWW'21
Google | [FM2](https://arxiv.org/abs/2102.12994) {cite}`FM2`
WWW'21
Yahoo | [EDCN](https://dlp-kdd.github.io/assets/pdf/DLP-KDD_2021_paper_12.pdf) {cite}`EDCN`
CIKM'21
Huawei | [DESTINE](https://arxiv.org/abs/2101.03654) {cite}`DESTINE`
CIKM'21
Alibaba |
| | [SAM](https://arxiv.org/abs/2105.05563) {cite}`SAM`
SIGIR'21
BOSS Zhipin | [PCF-GNN](https://arxiv.org/abs/2105.07752) {cite}`PCF-GNN`
SIGIR'21
Alibaba | [xLightFM](https://dl.acm.org/doi/10.1145/3404835.3462941) {cite}`xLightFM`
SIGIR'21 | [AOANet](https://dl.acm.org/doi/10.1145/3447548.3467133) {cite}`AOANet`
KDD'21
Didi Chuxing |
-| | [DCAP](https://arxiv.org/abs/2105.08649) {cite}`DCAP`
CIKM'21 | |
+| | [DCAP](https://arxiv.org/abs/2105.08649) {cite}`DCAP`
CIKM'21 | [xDeepInt](https://arxiv.org/abs/2301.01089) {cite}`xDeepInt`
DLP-KDD'21
Credit Karma |
| **2020** | [AFN](https://ojs.aaai.org/index.php/AAAI/article/view/5768) {cite}`AFN`
AAAI'20 | [DeepIM](https://dl.acm.org/doi/10.1145/3340531.3412077) {cite}`DeepIM`
CIKM'20
Alibaba | [AutoGroup](https://dl.acm.org/doi/abs/10.1145/3397271.3401082) {cite}`AutoGroup`
SIGIR'20
Huawei | [FWL](https://arxiv.org/abs/2012.00202) {cite}`FWL`
NeurIPS'20 |
| | [ONN](https://arxiv.org/pdf/1904.12579) {cite}`ONN`
NeuralNets'20 | [DIFM](https://www.ijcai.org/Proceedings/2020/0434.pdf) {cite}`DIFM`
IJCAI'20 | [AutoFIS](https://arxiv.org/abs/2003.11235) {cite}`AutoFIS`
KDD'20
Huawei | [AutoCTR](https://arxiv.org/abs/2007.06434) {cite}`AutoCTR`
KDD'20
Facebook |
| |[GLIDER](https://arxiv.org/abs/2006.10966) {cite}`GLIDER`
ICLR'20
Facebook |
@@ -41,10 +41,13 @@ A curated list of CTR prediction models
| | | | | | |
| :---------:|:------:|:------:|:------:|:------:|:------:|
-| **2023** | [SATrans](https://dl.acm.org/doi/10.1145/3580305.3599936) {cite}`SATrans`
KDD'23
Tencent |
-| **2021** | [STAR](https://arxiv.org/abs/2101.11427) {cite}`STAR`
CIKM'21
Alibaba | [DASL](https://arxiv.org/abs/2106.02768) {cite}`DASL`
KDD'21
Alibaba |
+| **2023** | [SATrans](https://dl.acm.org/doi/10.1145/3580305.3599936) {cite}`SATrans`
KDD'23
Tencent | [DFFM](https://dl.acm.org/doi/10.1145/3583780.3615469) {cite}`DFFM`
CIKM'23
Huawei |
+| **2022** | [M2M](https://arxiv.org/pdf/2201.06814) {cite}`M2M`
WSDM'22
Alibaba |
+| **2021** | [STAR](https://arxiv.org/abs/2101.11427) {cite}`STAR`
CIKM'21
Alibaba | [DASL](https://arxiv.org/abs/2106.02768) {cite}`DASL`
KDD'21
Alibaba | [GemNN](https://github.com/tangxyw/RecSysPapers/blob/main/Industry/CreativeSelection/%5B2021%5D%5BBaidu%5D%5BGemNN%5D%20GemNN%20-%20Gating-Enhanced%20Multi-Task%20Neural%20Networks%20with%20Feature%20Interaction%20Learning%20for%20CTR%20Prediction.pdf) {cite}`GemNN`
SIGIR'21
Baidu | [MTMS](https://github.com/tangxyw/RecSysPapers/blob/main/Multi-Scenario/%5B2021%5D%5BBaidu%5D%20Multi-Task%20and%20Multi-Scene%20Unified%20Ranking%20Model%20for%20Online%20Advertising.pdf) {cite}`MTMS`
BigData'21
Baidu |
| **2019** | [DeepMCP](https://arxiv.org/abs/1906.04365) {cite}`DeepMCP`
IJCAI'19
Alibaba |
+
+
## Embedding Learning
| | | | | | |
@@ -52,12 +55,13 @@ A curated list of CTR prediction models
| **2021** | [AutoDis](https://arxiv.org/abs/2012.08986) {cite}`AutoDis`
KDD'21
Huawei | [DG-ENN](https://arxiv.org/abs/2106.00314) {cite}`DG-ENN`
KDD'21
Huawei | [GME](https://arxiv.org/abs/2105.08909) {cite}`GME`
KDD'21
Alibaba |
| **2019** | [MetaEmbedding](https://arxiv.org/abs/1904.11547) {cite}`MetaEmbedding`
SIGIR'19 |
-## Pretraining
+## Pre-training
| | | | | | |
| :---------:|:------:|:------:|:------:|:------:|:------:|
-| **2023** | [MAP](https://arxiv.org/abs/2308.01737) {cite}`MAP`
KDD'23
Huawei | [BERT4CTR](https://arxiv.org/abs/2308.11527) {cite}`BERT4CTR`
KDD'23
Microsoft |
-
+| **2023** | [MAP](https://arxiv.org/abs/2308.01737) {cite}`MAP`
KDD'23
Huawei | [BERT4CTR](https://arxiv.org/abs/2308.11527) {cite}`BERT4CTR`
KDD'23
Microsoft | [SUM](https://arxiv.org/abs/2311.09544) {cite}`SUM`
Arxiv'23
Meta | [UniM^2Rec](https://arxiv.org/abs/2311.01831) {cite}`UniM2Rec`
Arxiv'23
Tencent |
+| | [SGP](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) {cite}`SGP`
AdKDD'23
Amazon |
+| **2022** | [GUIM](https://arxiv.org/abs/2207.00750) {cite}`GUIM`
Arxiv'22
Alibaba |
## References
diff --git a/docs/CTR/references.bib b/docs/CTR/references.bib
index 82e5f8c..71209e6 100644
--- a/docs/CTR/references.bib
+++ b/docs/CTR/references.bib
@@ -289,7 +289,8 @@ @inproceedings{DCN
Gang Fu and
Mingliang Wang},
title = {{Deep {\&} Cross Network for Ad Click Predictions}},
- booktitle = {Proceedings of the ADKDD '17},
+ booktitle = {Proceedings of the Workshop on Data Mining for Online Advertising
+ (AdKDD '17)},
pages = {12:1--12:7},
year = {2017},
}
@@ -1122,3 +1123,172 @@ @inproceedings{BERT4CTR
pages = {5039--5050},
year = {2023},
}
+
+@inproceedings{DFFM,
+ author = {Wei Guo and
+ Chenxu Zhu and
+ Fan Yan and
+ Bo Chen and
+ Weiwen Liu and
+ Huifeng Guo and
+ Hongkun Zheng and
+ Yong Liu and
+ Ruiming Tang},
+ title = {{{DFFM:} Domain Facilitated Feature Modeling for {CTR} Prediction}},
+ booktitle = {Proceedings of the 32nd {ACM} International Conference on Information
+ and Knowledge Management ({CIKM} '23)},
+ pages = {4602--4608},
+ year = {2023},
+}
+
+@inproceedings{DHEN,
+ author = {Buyun Zhang and
+ Liang Luo and
+ Xi Liu and
+ Jay Li and
+ Zeliang Chen and
+ Weilin Zhang and
+ Xiaohan Wei and
+ Yuchen Hao and
+ Michael Tsang and
+ Wenjun Wang and
+ Yang Liu and
+ Huayu Li and
+ Yasmine Badr and
+ Jongsoo Park and
+ Jiyan Yang and
+ Dheevatsa Mudigere and
+ Ellie Wen},
+ title = {{{DHEN:} {A} Deep and Hierarchical Ensemble Network for Large-Scale
+ Click-Through Rate Prediction}},
+ booktitle = {Proceedings of the 4th Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD ({DLP-KDD} '22)},
+ year = {2022},
+}
+
+@article{SUM,
+ author = {Wei Zhang and
+ Dai Li and
+ Chen Liang and
+ Fang Zhou and
+ Zhongke Zhang and
+ Xuewei Wang and
+ Ru Li and
+ Yi Zhou and
+ Yaning Huang and
+ Dong Liang and
+ Kai Wang and
+ Zhangyuan Wang and
+ Zhengxing Chen and
+ Min Li and
+ Fenggang Wu and
+ Minghai Chen and
+ Huayu Li and
+ Yunnan Wu and
+ Zhan Shu and
+ Mindi Yuan and
+ Sri Reddy},
+ title = {{Scaling User Modeling: Large-scale Online User Representations for
+ Ads Personalization in Meta}},
+ journal = {CoRR},
+ volume = {abs/2311.09544},
+ year = {2023},
+}
+
+@article{UniM2Rec,
+ author = {Wenqi Sun and
+ Ruobing Xie and
+ Shuqing Bian and
+ Wayne Xin Zhao and
+ Jie Zhou},
+ title = {{Universal Multi-modal Multi-domain Pre-trained Recommendation}},
+ journal = {CoRR},
+ volume = {abs/2311.01831},
+ year = {2023},
+}
+
+@article{GUIM,
+ author = {Chao Yang and
+ Ru He and
+ Fangquan Lin and
+ Suoyuan Song and
+ Jingqiao Zhang and
+ Cheng Yang},
+ title = {{{GUIM} - General User and Item Embedding with Mixture of Representation
+ in E-commerce}},
+ journal = {CoRR},
+ volume = {abs/2207.00750},
+ year = {2022}
+}
+
+@inproceedings{AdaEnsemble,
+ author = {YaChen Yan and
+ Liubo Li},
+ title = {{AdaEnsemble: Learning Adaptively Sparse Structured Ensemble Network
+ for Click-Through Rate Prediction}},
+ booktitle = {Proceedings of the Workshop on Data Mining for Online Advertising
+ (AdKDD '23)},
+ year = {2023},
+}
+
+@inproceedings{SGP,
+ author = {Sharad Chitlangia and
+ Krishna Reddy Kesari and
+ Rajat Agarwal},
+ title = {{Scaling Generative Pre-training for User Ad Activity Sequences}},
+ booktitle = {Proceedings of the Workshop on Data Mining for Online Advertising
+ (AdKDD '23)},
+ volume = {3556},
+ year = {2023},
+}
+
+@inproceedings{xDeepInt,
+ author = {YaChen Yan and
+ Liubo Li},
+ title = {{xDeepInt: A Hybrid Architecture for Modeling the Vector-wise and Bit-wise
+ Feature Interactions}},
+ booktitle = {Proceedings of the 3rd Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD ({DLP-KDD} '21)},
+ year = {2021},
+}
+
+@inproceedings{GemNN,
+ author = {Hongliang Fei and
+ Jingyuan Zhang and
+ Xingxuan Zhou and
+ Junhao Zhao and
+ Xinyang Qi and
+ Ping Li},
+ title = {{GemNN: Gating-enhanced Multi-task Neural Networks with Feature Interaction
+ Learning for {CTR} Prediction}},
+ booktitle = {The 44th International {ACM} {SIGIR} Conference on Research
+ and Development in Information Retrieval ({SIGIR} '21)},
+ pages = {2166--2171},
+ year = {2021},
+}
+
+@inproceedings{MTMS,
+ author = {Shulong Tan and
+ Meifang Li and
+ Weijie Zhao and
+ Yandan Zheng and
+ Xin Pei and
+ Ping Li},
+ title = {{Multi-Task and Multi-Scene Unified Ranking Model for Online Advertising}},
+ booktitle = {{IEEE} International Conference on Big Data (BigData '21)},
+ pages = {2046--2051},
+ year = {2021},
+}
+
+@inproceedings{M2M,
+ author = {Qianqian Zhang and
+ Xinru Liao and
+ Quan Liu and
+ Jian Xu and
+ Bo Zheng},
+ title = {{Leaving No One Behind: {A} Multi-Scenario Multi-Task Meta Learning
+ Approach for Advertiser Modeling}},
+ booktitle = {The Fifteenth {ACM} International Conference on Web Search
+ and Data Mining ({WSDM} '22)},
+ pages = {1368--1376},
+ year = {2022},
+}
+
diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03.csv b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03.csv
similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03.yaml b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03.yaml
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rename to ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/dataset_config.yaml b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/dataset_config.yaml
similarity index 100%
rename from ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/dataset_config.yaml
rename to ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/dataset_config.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/model_config.yaml b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt+_amazonelectronics_x1_tuner_config_03/model_config.yaml
similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/AutoInt_amazonelectronics_x1_004_7a937c94.log b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/AutoInt_amazonelectronics_x1_004_7a937c94.log
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diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/README.md b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/README.md
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diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/environments.txt b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/environments.txt
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diff --git a/ranking/ctr/AutoInt/AutoInt_amazonelectronics_x1/results.csv b/ranking/ctr/AutoInt/AutoInt+_amazonelectronics_x1/results.csv
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diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02.csv b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02.csv
similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02.yaml b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02.yaml
similarity index 100%
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rename to ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/dataset_config.yaml b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/dataset_config.yaml
similarity index 100%
rename from ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/dataset_config.yaml
rename to ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/dataset_config.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/model_config.yaml b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/model_config.yaml
similarity index 100%
rename from ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/model_config.yaml
rename to ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt+_kuaivideo_x1_tuner_config_02/model_config.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/AutoInt_kuaivideo_x1_011_9ed2831b.log b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/AutoInt_kuaivideo_x1_011_9ed2831b.log
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diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/README.md b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/README.md
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similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_kuaivideo_x1/results.csv b/ranking/ctr/AutoInt/AutoInt+_kuaivideo_x1/results.csv
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08.csv b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08.csv
similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08.yaml b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08.yaml
similarity index 100%
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rename to ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08.yaml
diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08/dataset_config.yaml b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08/dataset_config.yaml
similarity index 100%
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08/model_config.yaml b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt+_microvideo1.7m_x1_tuner_config_08/model_config.yaml
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/AutoInt_microvideo1.7m_x1_029_f813da5f.log b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/AutoInt_microvideo1.7m_x1_029_f813da5f.log
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/README.md b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/README.md
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diff --git a/ranking/ctr/AutoInt/AutoInt_microvideo1.7m_x1/results.csv b/ranking/ctr/AutoInt/AutoInt+_microvideo1.7m_x1/results.csv
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diff --git a/ranking/ctr/AutoInt/AutoInt_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02.csv b/ranking/ctr/AutoInt/AutoInt+_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02.csv
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diff --git a/ranking/ctr/AutoInt/AutoInt_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02.yaml b/ranking/ctr/AutoInt/AutoInt+_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02.yaml
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diff --git a/ranking/ctr/AutoInt/AutoInt_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02/dataset_config.yaml b/ranking/ctr/AutoInt/AutoInt+_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02/dataset_config.yaml
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diff --git a/ranking/ctr/AutoInt/AutoInt_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02/model_config.yaml b/ranking/ctr/AutoInt/AutoInt+_taobaoad_x1/AutoInt+_taobaoad_x1_tuner_config_02/model_config.yaml
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diff --git a/ranking/ctr/AutoInt/AutoInt_taobaoad_x1/AutoInt_taobaoad_x1_012_778cf7e5.log b/ranking/ctr/AutoInt/AutoInt+_taobaoad_x1/AutoInt_taobaoad_x1_012_778cf7e5.log
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