activity
20242026
collaborators

17 papers

cs.LG2026

MARA: Flow-Matching-Guided Multi-Agent Resource Allocation for Computational Resource Efficient Learning

Hanye Zhao, Muning Wen, Yong Yu +1

Allocating limited computation among concurrent learning tasks is difficult when each task must reach a target loss before a deadline but its required training effort is unknown. E…

cs.MA2026

MAPLE-Guard: Memory-Aware Link Enforcement Against Memory-Link Poisoning in Multi-Agent Systems

Wenjun Xiong, Yijin Zhou, Jiaqian Wang +6

LLM-based multi-agent systems (MAS) increasingly rely on persistent private and shared memories for long-horizon coordination. This memory layer improves continuity, but it also gi…

cs.MA2026

MARFT: Multi-Agent Reinforcement Fine-Tuning

Junwei Liao, Muning Wen, Jun Wang +1

Large Language Model (LLM)-based Multi-Agent Systems (LaMAS) have demonstrated strong capabilities on complex agentic tasks requiring multifaceted reasoning and collaboration, from…

cs.AI2026

MemQ: Integrating Q-Learning into Self-Evolving Memory Agents over Provenance DAGs

Junwei Liao, Haoting Shi, Ruiwen Zhou +9

Episodic memory allows LLM agents to accumulate and retrieve experience, but current methods treat each memory independently, i.e., evaluating retrieval quality in isolation withou…

cs.AI2026

Position: Agentic AI System Is a Foreseeable Pathway to AGI

Junwei Liao, Shuai Li, Muning Wen +2

Is monolithic scaling the only path to AGI? This paper challenges the dogma that purely scaling a single model is sufficient to achieve Artificial General Intelligence. Instead, we…

cs.AI2026

CreativeGame:Toward Mechanic-Aware Creative Game Generation

Hongnan Ma, Han Wang, Shenglin Wang +6

Large language models can generate plausible game code, but turning this capability into \emph{iterative creative improvement} remains difficult. In practice, single-shot generatio…