Li, Longfei

19 publications

ICLR 2025 Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization XiaoHua Feng, Yuyuan Li, Chaochao Chen, Li Zhang, Longfei Li, Jun Zhou, Xiaolin Zheng

NeurIPS 2025 Martian World Model: Controllable Video Synthesis with Physically Accurate 3D Reconstructions Longfei Li, Zhiwen Fan, Wenyan Cong, Xinhang Liu, Yuyang Yin, Matt Foutter, Panwang Pan, Chenyu You, Yue Wang, Zhangyang Wang, Yao Zhao, Marco Pavone, Yunchao Wei

AAAI 2024 Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations Junpeng Fang, Gongduo Zhang, Qing Cui, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou

NeurIPS 2024 Collaborative Refining for Learning from Inaccurate Labels Bin Han, Yi-Xuan Sun, Ya-Lin Zhang, Libang Zhang, Haoran Hu, Longfei Li, Jun Zhou, Guo Ye, Huimei He

AAAI 2024 LLMRG: Improving Recommendations Through Large Language Model Reasoning Graphs Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li

ICML 2024 Self-Cognitive Denoising in the Presence of Multiple Noisy Label Sources Yi-Xuan Sun, Ya-Lin Zhang, Bin Han, Longfei Li, Jun Zhou

AAAI 2024 Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li

AAAI 2024 Π-Light: Programmatic Interpretable Reinforcement Learning for Resource-Limited Traffic Signal Control Yin Gu, Kai Zhang, Qi Liu, Weibo Gao, Longfei Li, Jun Zhou

ICML 2023 Difference-in-Differences Meets Tree-Based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Longfei Li, Jun Zhou

NeurIPS 2023 FAST: A Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation Jia Gu, Caizhi Tang, Han Yan, Qing Cui, Longfei Li, Jun Zhou

IJCAI 2023 Keep Skills in Mind: Understanding and Implementing Skills in Commonsense Question Answering Meikai Bao, Qi Liu, Kai Zhang, Ye Liu, Linan Yue, Longfei Li, Jun Zhou

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

NeurIPS 2022 Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang

ACML 2022 Robust Direct Learning for Causal Data Fusion Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou

AAAI 2022 SAIL: Self-Augmented Graph Contrastive Learning Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang

IJCAI 2021 Cross-Domain Recommendation: Challenges, Progress, and Prospects Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu

ECML-PKDD 2020 AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models Qing Cui, Qitao Shi, Hao Qian, Caizhi Tang, Xixi Li, Yiming Zhao, Tao Jiang, Longfei Li, Jun Zhou

ICLR 2020 Knowledge Consistency Between Neural Networks and Beyond Ruofan Liang, Tianlin Li, Longfei Li, Jing Wang, Quanshi Zhang

AAAI 2019 GeniePath: Graph Neural Networks with Adaptive Receptive Paths Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi