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Xiangyu Wen

ACL 2026×2ICLR 2026×2推理强化学习与后训练效率与系统可解释性对齐与偏好
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1 一作 · 4 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

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

Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier

Jianyuan Zhong · Zeju Li · Zhijian Xu · Xiangyu Wen · Kezhi Li · Qiang Xu

摘要

Complex reasoning with Large Language Models (LLMs) demands a careful balance between accuracy and computational cost. Verification is crucial for reliability but faces trade-off: robust process-based verifiers are computationally prohibitive, while fast verifiers lack precision. We introduce fle...

强化学习与后训练推理可解释性OpenReview 项目页
作者位次 #5/8ACL 2026Findings· Findings of ACL

Beyond Overlap Metrics: Rewarding Reasoning and Preferences for Faithful Multi-Role Dialogue Summarization

Xiaoyong Mei · Tingting Zuo · Da Chen · Guangyu Hu · Xiangyu Wen · Chao Duan · Mingyan Zhang · Fudan Zheng

摘要

Multi-role dialogue summarization requires modeling complex interactions among multiple speakers while preserving role-specific information and factual consistency. However, most existing methods optimize for automatic metrics such as ROUGE and BERTScore, which favor surface-level imitation of re...

强化学习与后训练对齐与偏好推理OpenReview 项目页

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