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Ziqiang Liu

ACL 2026×2评测与基准对齐与偏好强化学习与后训练推理检索与知识
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #8/13ACL 2026Poster· Natural Language Processing

Act-Adaptive Margin: Dynamically Calibrating Reward Models for Subjective Ambiguity

Feiteng Fang · Dingwei Chen · Xiang Huang · Ting-En Lin · Yuchuan Wu · Xiong Liu · Jing Ye · Ziqiang Liu · Haonan Zhang · Liang Zhu · Hamid Alinejad-Rokny · Min Yang · Yongbin Li

摘要

Currently, most reinforcement learning tasks focus on domains like mathematics and programming, where verification is relatively straightforward. However, in subjective tasks such as role-playing, alignment techniques struggle to make progress, primarily because subjective reward modeling using t...

对齐与偏好强化学习与后训练评测与基准OpenReview 项目页
作者位次 #12/23ACL 2026Findings· Findings of ACL

Towards IP Intelligence: Benchmarking Large Language Models on Intellectual Property Knowledge and Practice

Qiyao Wang · Guhong Chen · Hongbo Wang · Huaren Liu · Minghui Zhu · Zhifei Qin · Li Linwei · Yilin Yue · Shiqiang Wang · Jiayan Li · Wu Yihang · Ziqiang Liu · Longze Chen · Run Luo · Liyang Fan · Jiaming Li · Lei Zhang · Kan Xu · Hamid Alinejad-Rokny · Chengming Li · Shiwen Ni · Yuan Lin · Min Yang

摘要

Intellectual Property (IP) is a highly specialized domain that integrates technical and legal knowledge, making it inherently complex and knowledge-intensive. Recent advancements in LLMs have demonstrated their potential to handle IP tasks, enabling more efficient analysis, understanding, and gen...

推理评测与基准检索与知识OpenReview 项目页

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