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Yuhao Zhou

ACL 2026×2ICLR 2026×2CVPR 2026KDD 2026评测与基准多模态推理检索与知识强化学习与后训练
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一作贡献30
核心/参与36
方向广度19
合作网络9
1 一作 · 6 篇 · ACL 2026 / ICLR 2026 / CVPR 2026 / KDD 2026

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2026 顶会论文

6
一作ICLR 2026Poster· Deep Learning / Everything Else

Deploying Models to Non-participating Clients in Federated Learning without Fine-tuning: A Hypernetwork-based Approach

Yuhao Zhou · Jindi Lv · Yuxin Tian · Dan Si · Qing Ye · Jiancheng Lv

强化学习与后训练OpenReview
作者位次 #4/10ACL 2026Poster· Natural Language Processing

MSE arth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLM s

Xiangyu Zhao · Wanghan Xu · Bo LIU · Yuhao Zhou · Fenghua Ling · Ben Fei · Xiaoyu Yue · LEI BAI · Wenlong Zhang · Xiao-Ming Wu

摘要

The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application in earth science—especially at the graduate level—remains underexplored due to a lack of benchmarks reflecting the depth and complexity of geoscienti...

多模态评测与基准数据与预训练OpenReview 项目页
作者位次 #6/14ACL 2026Poster· Natural Language Processing

F low S earch: Advancing Deep Research with Dynamic Structured Knowledge Flow

Yusong Hu · Runmin Ma · Yue Fan · Jinxin Shi · Zongsheng Cao · Yuhao Zhou · Jiakang Yuan · Shuaiyu Zhang · Shiyang Feng · Xiangchao Yan · Shufei Zhang · Wenlong Zhang · LEI BAI · Bo Zhang

摘要

Deep research is an inherently challenging task that demands both breadth and depth of thinking. It involves navigating diverse knowledge spaces and reasoning over complex, multi-step dependencies, which presents substantial challenges for agentic systems. To address this, we propose FlowSearch,...

推理智能体与工具检索与知识OpenReview 项目页

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