Wu, Chuhan

11 publications

NeurIPS 2025 P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models Tingjia Shen, Hao Wang, Chuhan Wu, Jin Yao Chin, Wei Guo, Yong Liu, Huifeng Guo, Defu Lian, Ruiming Tang, Enhong Chen

ICLR 2025 RevisEval: Improving LLM-as-a-Judge via Response-Adapted References Qiyuan Zhang, Yufei Wang, Tiezheng Yu, Yuxin Jiang, Chuhan Wu, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Fuyuan Lyu, Chen Ma

ICLR 2025 ToolACE: Winning the Points of LLM Function Calling Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Wang Xinzhi, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen

NeurIPS 2022 FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie

ECCV 2022 FedX: Unsupervised Federated Learning with Cross Knowledge Distillation Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha

IJCAI 2022 Rethinking InfoNCE: How Many Negative Samples Do You Need? Chuhan Wu, Fangzhao Wu, Yongfeng Huang

AAAI 2021 Fairness-Aware News Recommendation with Decomposed Adversarial Learning Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, Xing Xie

IJCAI 2021 User-as-Graph: User Modeling with Heterogeneous Graph Pooling for News Recommendation Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie

IJCAI 2020 User Modeling with Click Preference and Reading Satisfaction for News Recommendation Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang

AAAI 2019 Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning Ji Zhao, Dan Peng, Chuhan Wu, Huan Chen, Meiyu Yu, Wanji Zheng, Li Ma, Hua Chai, Jieping Ye, Xiaohu Qie

IJCAI 2019 Neural News Recommendation with Attentive Multi-View Learning Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie