From the 2 of 7 linked papers with an AI index.
7 papers
When Does Muon Help Agentic Reinforcement Learning?
Kai Ruan, Jinghao Lin, Zihe Huang +4
Muon is competitive with AdamW in large-scale pre-training, but its operating regime in reinforcement-learning post-training remains unclear. We map this regime on ALFWorld, a spar…
Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade
Kai Ruan, Zihe Huang, Ziqi Zhou +4
The paper proposes using lightweight linear probes on hidden states of large language model agents to predict failures early and abort doomed episodes, achieving large compute savi…
The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy
Chunzheng Zhu, Lei Tian, Bohan Tan +16
The paper outlines a roadmap for developing medical AI agents that move from assisting clinicians to operating autonomously, focusing on scaling frameworks, capabilities, and clini…
SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation
Zhengbo Jiao, Yiming Cheng, Yilei Jiang +15
Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines construct training data, search…
Toward Efficient Agents: Memory, Tool learning, and Planning
Xiaofang Yang, Lijun Li, Heng Zhou +12
Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has continued to improve, efficiency, whi…
Agentic-MME: What Agentic Capability Really Brings to Multimodal Intelligence?
Qianshan Wei, Yishan Yang, Siyi Wang +12
Multimodal Large Language Models (MLLMs) are evolving from passive observers into active agents, solving problems through Visual Expansion (invoking visual tools) and Knowledge Exp…