5 papers
Paying Less Generalization Tax: A Cross-Domain Generalization Study of RL Training for LLM Agents
Zhihan Liu, Lin Guan, Yixin Nie +6
Generalist LLM agents are often post-trained on a narrow set of environments but deployed across far broader, unseen domains. In this work, we investigate the challenge of agentic…
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Boyu Gou, Zanming Huang, Yuting Ning +23
Agentic search such as Deep Research systems-where agents autonomously browse the web, synthesize information, and return comprehensive citation-backed answers-represents a major s…
Is Extending Modality The Right Path Towards Omni-Modality?
Tinghui Zhu, Kai Zhang, Muhao Chen +1
Omni-modal language models (OLMs) aim to integrate and reason over diverse input modalities--such as text, images, video, and audio--while maintaining strong language capabilities.…
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
Yu Gu, Kai Zhang, Yuting Ning +9
Language agents based on large language models (LLMs) have demonstrated great promise in automating web-based tasks. Recent work has shown that incorporating advanced planning algo…
MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
Xiang Yue, Tianyu Zheng, Yuansheng Ni +10
This paper introduces MMMU-Pro, a robust version of the Massive Multi-discipline Multimodal Understanding and Reasoning (MMMU) benchmark. MMMU-Pro rigorously assesses multimodal mo…