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From the 1 of 28 linked papers with an AI index.

collaborators

28 papers

cs.AI2026

LatticeMind: A Conflict-Aware Memory Primitive for Multi-Agent Systems

Heng Zhou, Lian Zhang, Yutao Fan +5

Multi-agent LLM systems often fail not for lack of candidate answers, but because they have no persistent mechanism for deciding which incompatible claim should currently be truste…

cs.AI2026

SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation

Zelin Tan, Yiqun Zhang, Hao Li +11

Agent skills have become an important mechanism for equipping language-model agents with reusable procedural knowledge. However, providing skills alone does not guarantee that curr…

cs.CV2026

Exploratory, Communicative, and Deployable: Vision-Driven Embodied Agents for Open-World Mobile Manipulation

Boyu Mi, Mengchen Ma, Yifei Yao +10

The paper introduces REAL, a framework that trains embodied agents for open‑world mobile manipulation using sim‑to‑real consistent environments, hierarchical training, and human‑in…

cs.CL2026

SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks

Jingru Guo, Xiangyuan Xue, Lian Zhang +6

Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of expert-level performance. A clos…

cs.CL2026

MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems

Rui Ye, Keduan Huang, Qimin Wu +17

LLM-based multi-agent systems (MAS) have demonstrated significant potential in enhancing single LLMs to address complex and diverse tasks in practical applications. Despite conside…

cs.CL2026

SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents

Yujiong Shen, Yajie Yang, Zhiheng Xi +17

Scientific reasoning inherently demands integrating sophisticated toolkits to navigate domain-specific knowledge. Yet, current benchmarks largely overlook agents' ability to orches…