Jiahui Li

According to our database, Jiahui Li authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Path-Decoupled Hyperbolic Flow Matching for Few-Shot Adaptation.

Lin Li, Ziqi Jiang, Gefan Ye, Zhenqi He, Jiahui Li, Jun Xiao, Kwang-Ting Cheng, Long Chen

CoRR, February, 2026

Relation-R1: Progressively Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relation Comprehension.

Lin Li, Wei Chen, Jiahui Li, Kwang-Ting Cheng, Long Chen

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Relation-R1: Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relational Comprehension.

Lin Li, Wei Chen, Jiahui Li, Long Chen

CoRR, April, 2025

RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution.

Jiahui Li, Lin Li, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou, Cheng Yang

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards.

Zijing Hu, Fengda Zhang, Long Chen, Kun Kuang, Jiahui Li, Kaifeng Gao, Jun Xiao, Xin Wang, Wenwu Zhu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Learning Causal Transition Matrix for Instance-dependent Label Noise.

Jiahui Li, Tai-Wei Chang, Kun Kuang, Ximing Li, Long Chen, Jun Zhou

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

R3HF: Reward Redistribution for Enhancing Reinforcement Learning from Human Feedback.

Jiahui Li, Tai-Wei Chang, Fengda Zhang, Kun Kuang, Long Chen

CoRR, 2024

Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning.

Jiahui Li, Hanlin Zhang, Fengda Zhang, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning.

Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?

Shuang Luo, Yinchuan Li, Jiahui Li, Kun Kuang, Furui Liu, Yunfeng Shao, Chao Wu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning.

Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao

Proceedings of the International Conference on Machine Learning, 2022

2021

Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation.

Jiahui Li, Kun Kuang, Lin Li, Long Chen, Songyang Zhang, Jian Shao, Jun Xiao

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning.

Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021