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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CV2026

DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents

Huanyao Zhang, Jiepeng Zhou, Runhao Zhao +12

Multimodal large language models (MLLMs) have advanced visual understanding and reasoning, yet their static parametric knowledge limits their ability to address knowledge-intensive…

cs.CL2026

Knowledge before Reasoning: EC-Reason-Bench, a Training-Free Diagnostic Benchmark for LLM Enzyme Classification

Linyu Li, Zhi Jin, Yichi Zhang +6

The paper introduces EC-Reason-Bench, a training-free diagnostic benchmark that evaluates why general large language models struggle with detailed enzyme classification and how per…

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

BrowseComp-: A Visual, Vertical, and Verifiable Benchmark for Multimodal Browsing Agents

Huanyao Zhang, Jiepeng Zhou, Bo Li +22

Multimodal large language models (MLLMs), equipped with increasingly advanced planning and tool-use capabilities, are evolving into autonomous agents capable of performing multimod…

cs.CL2026

RAGShaper: Eliciting Sophisticated Agentic RAG Skills via Automated Data Synthesis

Zhengwei Tao, Bo Li, Jialong Wu +5

Agentic Retrieval-Augmented Generation (RAG) empowers large language models to autonomously plan and retrieve information for complex problem-solving. However, the development of r…

cs.CL2026

DocDancer: Towards Agentic Document-Grounded Information Seeking

Qintong Zhang, Xinjie Lv, Jialong Wu +8

Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and largely rely on closed…