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20242026
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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.AI2025

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…

cs.AI2025

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…

cs.AI2025

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…

cs.AI2025

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…