ML Anthology

Wu, Jiancan

13 publications

ICML 2025 AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization Junkang Wu, Xue Wang, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
NeurIPS 2025 Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation Guoqing Hu, An Zhang, Shuchang Liu, Wenyu Mao, Jiancan Wu, Xun Yang, Xiang Li, Lantao Hu, Han Li, Kun Gai, Xiang Wang
ICML 2025 Larger or Smaller Reward Margins to Select Preferences for LLM Alignment? Kexin Huang, Junkang Wu, Ziqian Chen, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang
NeurIPS 2025 On Efficiency-Effectiveness Trade-Off of Diffusion-Based Recommenders Wenyu Mao, Jiancan Wu, Guoqing Hu, Zhengyi Yang, Wei Ji, Xiang Wang
NeurIPS 2025 RePO: Understanding Preference Learning Through ReLU-Based Optimization Junkang Wu, Kexin Huang, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang
NeurIPS 2025 Think Before Recommendation: Autonomous Reasoning-Enhanced Recommender Xiaoyu Kong, Junguang Jiang, Bin Liu, Ziru Xu, Han Zhu, Jian Xu, Bo Zheng, Jiancan Wu, Xiang Wang
ICLR 2025 Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
ICLR 2025 Unified Parameter-Efficient Unlearning for LLMs Chenlu Ding, Jiancan Wu, Yancheng Yuan, Jinda Lu, Kai Zhang, Alex Su, Xiang Wang, Xiangnan He
NeurIPS 2024 $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$ Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
NeurIPS 2024 Customizing Language Models with Instance-Wise LoRA for Sequential Recommendation Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He
NeurIPS 2023 Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He
NeurIPS 2023 Understanding Contrastive Learning via Distributionally Robust Optimization Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He
NeurIPS 2023 Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He