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From the 1 of 15 linked papers with an AI index.

most citedOmniGAIA: Towards Native Omni-Modal AI Agents

1 citations · 1 across the 12 of their papers we have counts for

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cs.AI2026

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories

Shuai Shao, Kangning Zhang, Qingyao Li +7

Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…

cs.AI20261 cited

OmniGAIA: Towards Native Omni-Modal AI Agents

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +10

Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to interact with the world. However,…

cs.AI2026

MMSkills: Towards Multimodal Skills for General Visual Agents

Kangning Zhang, Shuai Shao, Qingyao Li +8

Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as textual prompts, executable co…

cs.AI2026

MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs

Kevin Wang, Anna Thöni, Benjamin Kempinski +50

Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…

cs.AI2025

Agent2World: Learning to Generate Symbolic World Models via Adaptive Multi-Agent Feedback

Mengkang Hu, Bowei Xia, Yuran Wu +9

Symbolic world models (e.g., PDDL domains or executable simulators) are central to model-based planning, but training LLMs to generate such world models is limited by the lack of l…