3 citations · 3 across the 26 of their papers we have counts for
11 papers · 1 filter
AgentAbstain: Do LLM Agents Know When Not to Act?
Xun Liu, Yi Evie Zhang, Vira Kasprova +5
Agent systems based on large language models (LLMs) are increasingly deployed for autonomous tasks, yet existing evaluations mostly focus on task success rather than whether agents…
A First-Principles Derivation of LLM Policy Optimization: From Expected Reward to GRPO and Its Structural Extensions
Jianghan Shen, Siqi Luo, Yue Li +9
Policy gradient algorithms for language models optimize the same objective , which has exactly two factors: the trajectory probability $p_θ(…
Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments
Yuxin Chen, Xiaodong Cai, Junfeng Fang +9
Recent advances in large language models (LLMs) have facilitated the widespread deployment of LLMs as interactive agents capable of reasoning, planning, and tool use. Despite stron…
VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
Yuxin Chen, Yi Zhang, Zhengzhou Cai +11
Large language models (LLMs) have evolved into interactive agents that collaborate with users in real-world tasks. Effective collaboration in such settings increasingly depends on…
VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing
Haoyuan Shi, Xiancong Ren, Yingji Zhang +9
Understanding how Vision-Language-Action (VLA) models transform multimodal knowledge into embodied control remains an open challenge. We present VLA-Trace, a progressive diagnostic…
Explicit Trait Inference for Multi-Agent Coordination
Suhaib Abdurahman, Etsuko Ishii, Katerina Margatina +3
LLM-based multi-agent systems (MAS) show promise on complex tasks but remain prone to coordination failures such as goal drift, error cascades, and misaligned behaviors. We propose…
CollabEval: Enhancing LLM-as-a-Judge via Multi-Agent Collaboration
Yiyue Qian, Shinan Zhang, Yun Zhou +3
Large Language Models (LLMs) have revolutionized AI-generated content evaluation, with the LLM-as-a-Judge paradigm becoming increasingly popular. However, current single-LLM evalua…
SAMULE: Self-Learning Agents Enhanced by Multi-level Reflection
Yubin Ge, Salvatore Romeo, Jason Cai +2
Despite the rapid advancements in LLM agents, they still face the challenge of generating meaningful reflections due to inadequate error analysis and a reliance on rare successful…
Optimizing LLM-Based Multi-Agent System with Textual Feedback: A Case Study on Software Development
Ming Shen, Raphael Shu, Anurag Pratik +4
We have seen remarkable progress in large language models (LLMs) empowered multi-agent systems solving complex tasks necessitating cooperation among experts with diverse skills. Ho…
A Study on Leveraging Search and Self-Feedback for Agent Reasoning
Karthikeyan K, Michelle Yuan, Elman Mansimov +6
Recent works have demonstrated that incorporating search during inference can significantly improve reasoning capabilities of language agents. Some approaches may make use of the g…
TReMu: Towards Neuro-Symbolic Temporal Reasoning for LLM-Agents with Memory in Multi-Session Dialogues
Yubin Ge, Salvatore Romeo, Jason Cai +4
Temporal reasoning in multi-session dialogues presents a significant challenge which has been under-studied in previous temporal reasoning benchmarks. To bridge this gap, we propos…