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Bo Li

ACL 2026×3ICLR 2026多模态强化学习与后训练检索与知识推理评测与基准
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0 一作 · 4 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

4
作者位次 #6/8ACL 2026Poster· Natural Language Processing

MMS earch- R 1: Incentivizing LMM s to Search

Jinming Wu · Zihao Deng · Wei Li · Yiding Liu · Bo You · Bo Li · Zejun MA · Ziwei Liu

摘要

Robust deployment of large multimodal models (LMMs) in real-world scenarios requires access to external knowledge sources, given the complexity and dynamic nature of real-world information. Existing approaches such as retrieval-augmented generation (RAG) and prompt engineered search agents rely o...

检索与知识多模态推理OpenReview 项目页
作者位次 #6/8ACL 2026Poster· Natural Language Processing

Video- MMMU : Evaluating Knowledge Acquisition from Multidisciplinary Professional Videos

Kairui Hu · Penghao Wu · Fanyi Pu · Wang Xiao · Xiang Yue · Bo Li · Yuanhan Zhang · Ziwei Liu

摘要

Humans acquire knowledge through three cognitive stages: perceiving information, comprehending knowledge, and adapting knowledge to solve novel problems. Videos serve as an effective medium for knowledge acquisition, facilitating a natural progression through these learning stages. However, exist...

多模态评测与基准社会与人本OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

MGPO : Thinking with Images via Multi-Turn Grounding-Based Reinforcement Learning

Xinyu Huang · Yuhao Dong · Weiwei Tian · Bo Li · Rui Feng · Ziwei Liu

摘要

State-of-the-art large multi-modal models (LMMs) face challenges when processing high-resolution images, as these inputs are converted into enormous visual tokens, many of which are irrelevant to the downstream task. In this paper, we propose Multi-turn Grounding-based Policy Optimization (MGPO),...

强化学习与后训练多模态OpenReview 项目页

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