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20242026
most citedTowards Effective GenAI Multi-Agent Collaboration: Design and Evaluation for Enterprise Applications

3 citations · 3 across the 26 of their papers we have counts for

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Showing 2026 · cs.AIShow all

7 papers · 2 filters

cs.AI2026

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…

cs.AI2026

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(…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…