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Ze Wang

ICLR 2026×3ACL 2026×2CVPR 2026多模态推理评测与基准强化学习与后训练智能体与工具
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0 一作 · 6 篇 · ICLR 2026 / ACL 2026 / CVPR 2026

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2026 顶会论文

6
作者位次 #6/9ACL 2026Poster· Natural Language Processing

Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning

Zhikun Xu · Xiaodong Yu · Ben Zhou · Jiang Liu · Jialian Wu · Ze Wang · Ximeng Sun · Hao Chen · Zicheng Liu

摘要

Recent large language models (LLMs) perform strongly on mathematical benchmarks yet often misapply lemmas, importing conclusions without validating assumptions. We formalize lemma-judging as a structured prediction task: given a statement and a candidate lemma, the model must output a preconditio...

推理强化学习与后训练评测与基准OpenReview 项目页
作者位次 #7/10ACL 2026Findings· Findings of ACL

DRIFT : Transferring Reasoning Priors for Efficient MLLM Fine-Tuning

Chao Huang · Zeliang Zhang · Jiang Liu · Ximeng Sun · Jialian Wu · Xiaodong Yu · Ze Wang · Chenliang Xu · Emad Barsoum · Zicheng Liu

摘要

Multimodal large language models (MLLMs) have made rapid progress, yet their reasoning ability often lags behind strong text-only LLMs. Bridging this gap typically requires large-scale multimodal reasoning data or reinforcement learning, incurring substantial cost. An appealing alternative is par...

推理强化学习与后训练对齐与偏好OpenReview 项目页

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