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cs.CL2025

More Vulnerable than You Think: On the Stability of Tool-Integrated LLM Agents

Weimin Xiong, Ke Wang, Yifan Song +4

Current evaluations of tool-integrated LLM agents typically focus on end-to-end tool-usage evaluation while neglecting their stability. This limits their real-world applicability,…

cs.CL2024

An Electoral Approach to Diversify LLM-based Multi-Agent Collective Decision-Making

Xiutian Zhao, Ke Wang, Wei Peng

Modern large language models (LLMs) have exhibited cooperative synergy on complex task-solving, and collective decision-making (CDM) is a pivotal component in LLM-based multi-agent…

cs.CL2024

ORCHID: A Chinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarization

Xiutian Zhao, Ke Wang, Wei Peng

Dialogue agents have been receiving increasing attention for years, and this trend has been further boosted by the recent progress of large language models (LLMs). Stance detection…

cs.CL2024

Measuring the Inconsistency of Large Language Models in Preferential Ranking

Xiutian Zhao, Ke Wang, Wei Peng

Despite large language models' (LLMs) recent advancements, their bias and hallucination issues persist, and their ability to offer consistent preferential rankings remains underexp…

cs.CL2024

AgentBank: Towards Generalized LLM Agents via Fine-Tuning on 50000+ Interaction Trajectories

Yifan Song, Weimin Xiong, Xiutian Zhao +6

Fine-tuning on agent-environment interaction trajectory data holds significant promise for surfacing generalized agent capabilities in open-source large language models (LLMs). In…

cs.CL2024

Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement

Weimin Xiong, Yifan Song, Xiutian Zhao +6

Large language model agents have exhibited exceptional performance across a range of complex interactive tasks. Recent approaches have utilized tuning with expert trajectories to e…