Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning. - Ke Jiang; Jia-Yu Yao; Xiaoyang Tan (NeurIPS, 2023)

LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples. - Jia-Yu Yao; Kun-Peng Ning; Zhen-Hui Liu; Munan Ning; Li Yuan (CoRR, 2023)

Peer-review-in-LLMs: Automatic Evaluation Method for LLMs in Open-environment. - Kun-Peng Ning; Shuo Yang; Yu-Yang Liu; Jia-Yu Yao; Zhen-Hui Liu; Yu Wang; Ming Pang; Li Yuan (CoRR, 2024)

Sparse Orthogonal Parameters Tuning for Continual Learning. - Kun-Peng Ning; Hai-Jian Ke; Yu-Yang Liu; Jia-Yu Yao; Yonghong Tian 001; Li Yuan 007 (CoRR, 2024)

Sequential Cooperative Distillation for Imbalanced Multi-Task Learning. - Quan Feng; Jia-Yu Yao; Ming-Kun Xie; Sheng-Jun Huang; Songcan Chen (J. Comput. Sci. Technol., 2024)

Is Parameter Collision Hindering Continual Learning in LLMs? - Shuo Yang; Kun-Peng Ning; Yu-Yang Liu; Jia-Yu Yao; Yong-Hong Tian 001; Yi-Bing Song; Li Yuan 007 (COLING, 2025)

PiCO: Peer Review in LLMs based on Consistency Optimization. - Kun-Peng Ning; Shuo Yang; Yuyang Liu; Jia-Yu Yao; Zhen-Hui Liu; Yonghong Tian 001; Yibing Song; Li Yuan 007 (ICLR, 2025)

GPT as a Monte Carlo Language Tree: A Probabilistic Perspective. - Kun-Peng Ning; Jia-Yu Yao; Yu-Yang Liu; Mu-Nan Ning; Li Yuan (CoRR, 2025)

AsFT: Anchoring Safety During LLM Fine-Tuning Within Narrow Safety Basin. - Shuo Yang; Qihui Zhang; Yuyang Liu; Yue Huang; Xiaojun Jia; Kun-Peng Ning; Jia-Yu Yao; Jigang Wang; Hailiang Dai; Yibing Song; Li Yuan (CoRR, 2025)