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Qianli Wang

ACL 2026×2多语言与语言学评测与基准检索与知识可解释性对齐与偏好
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1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
一作ACL 2026Poster· Natural Language Processing

Parallel Universes, Parallel Languages: A Comprehensive Study on LLM -based Multilingual Counterfactual Example Generation

Qianli Wang · Van Bach Nguyen · Yihong Liu · Fedor Splitt · Nils Feldhus · Christin Seifert · Hinrich Schuetze · Sebastian Möller · Vera Schmitt

摘要

Counterfactuals refer to minimally edited inputs that cause a model’s prediction to change, serving as a promising approach to explaining the model’s behavior. Large language models (LLMs) excel at generating English counterfactuals and demonstrate multilingual proficiency. However, their effecti...

多语言与语言学评测与基准检索与知识OpenReview 项目页
作者位次 #7/28ACL 2026Findings· Findings of ACL

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models

Hengyuan Zhang · Zhihao Zhang · Ercong Nie · Mingyang Wang · Zunhai Su · Yiwei Wang · Qianli Wang · Shuzhou Yuan · Xufeng Duan · Qibo Xue · Zeping Yu · Chenming Shang · Xiao Liang · Jing Xiong · Hui Shen · Chaofan Tao · Zhengwu Liu · Senjie Jin · Zhiheng Xi · Dongdong Zhang · Sophia Ananiadou · Tao Gui · Ruobing Xie · Hayden Kwok-Hay So · Hinrich Schuetze · Xuanjing Huang · Qi Zhang · Ngai Wong

摘要

Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat MI as an observational science, summarizing analytical insights while lacking a systematic framework for actionable...

可解释性对齐与偏好效率与系统OpenReview 项目页

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