3 papers
cs.IR2026
SearchArt: Training Long-Horizon Search Agent with Scalable Synthetic and Verified Task
Lang Mei, Xiaohan Yu, Chong Chen +27
Recent advances in large language models (LLMs) have enabled search agents to autonomously tackle complex tasks across extended search and reasoning horizons. However, training eff…
cs.AI2026
AgentOmnia: Scaling Agentic Models for Full-Scenario Applications
Hao Jiang, Gangtao Xin, Yingdi Huang +35
Large language model agents have advanced rapidly, yet progress remains fragmented across domains, capabilities, task difficulty, and interaction settings. We frame this as full-sc…
cs.CL2026
OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios
Chengyu Shen, Yujie Fu, Gangtao Xin +13
Large language models are increasingly evolving from text generators into general agents capable of understanding user requests, invoking external tools, and completing complex tas…