5 papers
Diagnosing Task Insensitivity in Language Agents
Jingyu Liu, Xiaopeng Wu, Kehan Chen +2
Large language models can serve as capable long-horizon agents, but their out-of-distribution (OOD) generalization remains weak. We identify a key source of this failure as task in…
Gradient Coupling: The Hidden Barrier to Generalization in Agentic Reinforcement Learning
Jingyu Liu, Xiaopeng Wu, Jingquan Peng +4
Reinforcement learning (RL) is a dominant paradigm for training autonomous agents, yet these agents often exhibit poor generalization, failing to adapt to scenarios not seen during…
Mem-PAL: Towards Memory-based Personalized Dialogue Assistants for Long-term User-Agent Interaction
Zhaopei Huang, Qifeng Dai, Guozheng Wu +7
With the rise of smart personal devices, service-oriented human-agent interactions have become increasingly prevalent. This trend highlights the need for personalized dialogue assi…
Do not Abstain! Identify and Solve the Uncertainty
Jingyu Liu, Jingquan Peng, xiaopeng Wu +4
Despite the widespread application of Large Language Models (LLMs) across various domains, they frequently exhibit overconfidence when encountering uncertain scenarios, yet existin…
Enhancing Item Tokenization for Generative Recommendation through Self-Improvement
Runjin Chen, Mingxuan Ju, Ngoc Bui +7
Generative recommendation systems, driven by large language models (LLMs), present an innovative approach to predicting user preferences by modeling items as token sequences and ge…