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[ACL-2026] MMSearch-R1 is an end-to-end RL framework that enables LMMs to perform on-demand, multi-turn search with real-world multimodal search tools.
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R1-searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
ZeroSearch: Incentivize the Search Capability of LLMs without Searching
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning & ReCall: Learning to Reason with Tool Call for LLMs via Reinforcement Learning
MMaDA - Open-Sourced Multimodal Large Diffusion Language Models (dLLMs with block diffusion, mixed-CoT, unified RL)
R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning
