collaborators

5 papers

cs.AI2026

When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems

Zehao Wang, Shilong Jin, Zhao Cao +1

LLM-based multi-agent systems can fail even when planned actions are executed correctly because agents may misjudge their knowledge when evaluating plan feasibility, a phenomenon w…

cs.LG2026

SE-GA: Memory-Augmented Self-Evolution for GUI Agents

Shilong Jin, Lanjun Wang, Zhuosheng Zhang

Autonomous Graphical User Interface (GUI) agents often struggle with multi-step tasks due to constrained context windows and static policies that fail to adapt to dynamic environme…

cs.AI2025

Key Decision-Makers in Multi-Agent Debates: Who Holds the Power?

Qian Zhang, Yan Zheng, Jinyi Liu +2

Recent studies on LLM agent scaling have highlighted the potential of Multi-Agent Debate (MAD) to enhance reasoning abilities. However, the critical aspect of role allocation strat…

cs.CL2025

Exploring and Mitigating Fawning Hallucinations in Large Language Models

Zixuan Shangguan, Yanjie Dong, Lanjun Wang +3

Large language models (LLMs) have demonstrated exceptional proficiency in language understanding. However, when LLMs align their outputs with deceptive and/or misleading prompts, t…

cs.LG2025

MetaEformer: Unveiling and Leveraging Meta-patterns for Complex and Dynamic Systems Load Forecasting

Shaoyuan Huang, Tiancheng Zhang, Zhongtian Zhang +3

Time series forecasting is a critical and practical problem in many real-world applications, especially for industrial scenarios, where load forecasting underpins the intelligent o…