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Minghe Yu

ACL 2026×2ICLR 2026SIGIR 2026检索与知识强化学习与后训练多模态社会与人本智能体与工具
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合作网络12
0 一作 · 4 篇 · ACL 2026 / ICLR 2026 / SIGIR 2026

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2026 顶会论文

4
作者位次 #5/9ACL 2026Findings· Findings of ACL

Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling

Shuliang Liu · Zhipeng Xu · Zhenghao Liu · Yukun Yan · Minghe Yu · Yu Gu · an Jiaotong University) · Huiyuan Xie · Ge Yu

摘要

Large Language Models (LLMs) as automatic evaluators, commonly referred to as LLM-as-a-Judge, have also attracted growing attention. This approach plays a vital role in aligning LLMs with human judgments, providing accurate and reliable assessments. However, LLM-based judgment models often exhibi...

社会与人本智能体与工具对齐与偏好OpenReview 项目页
作者位次 #6/10ACL 2026Findings· Findings of ACL

Enhancing Long-Chain Reasoning Distillation through Error-Aware Self-Reflection

Zhuoyang Wu · Xinze Li · Zhenghao Liu · Yukun Yan · Zhiyuan Liu · Minghe Yu · Cheng Yang · Yu Gu · Ge Yu · Maosong Sun

摘要

Large Language Models (LLMs) have exhibited strong reasoning capabilities and achieved remarkable performance in mathematical problem-solving tasks. Recently, distilling reasoning ability from long-form Chains-of-Thought (CoTs) has emerged as a promising approach for enhancing Small Language Mode...

推理强化学习与后训练多模态OpenReview 项目页
作者位次 #8/10SIGIR 2026Oral· Information Retrieval (Full)

Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation

Chunyi Peng · Zhipeng Xu · Zhenghao Liu · Yishan Li · Yukun Yan · Shuo Wang · Yu Gu · Minghe Yu · Ge Yu · Maosong Sun

摘要

Multimodal Retrieval-Augmented Generation (MRAG) has shown promise in mitigating hallucinations in Multimodal Large Language Models (MLLMs) by incorporating external knowledge. However, existing methods typically adhere to rigid retrieval paradigms by mimicking fixed retrieval trajectories and th...

多模态强化学习与后训练检索与知识OpenReview

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