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20242026
most citedLarge Language Models for Automated Literature Review: An Evaluation of Reference Generation, Abstract Writing, and Review Composition

2 citations · 3 across the 13 of their papers we have counts for

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cs.CL2026

Do Large Language Models Plan Answer Positions? Position Bias in Multiple-Choice Question Generation

Xuemei Tang, Xufeng Duan, Zhenguang G. Cai

Large language models (LLMs) are increasingly used to generate multiple-choice questions (MCQs), where correct answers should ideally be uniformly distributed across options. Howev…

cs.CL2026

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

Hengyuan Zhang, Zhihao Zhang, Mingyang Wang +26

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…

cs.CL2025

Information Loss in LLMs' Multilingual Translation: The Role of Training Data, Language Proximity, and Language Family

Yumeng Lin, Xufeng Duan, David Haslett +2

Large language models have achieved impressive progress in multilingual translation, yet they continue to face challenges with certain language pairs-particularly those with limite…

cs.CL2025

How Syntax Specialization Emerges in Language Models

Xufeng Duan, Zhaoqian Yao, Yunhao Zhang +2

Large language models (LLMs) have been found to develop surprising internal specializations: Individual neurons, attention heads, and circuits become selectively sensitive to synta…

cs.CL2025

Distinct social-linguistic processing between humans and large audio-language models: Evidence from model-brain alignment

Hanlin Wu, Xufeng Duan, Zhenguang Cai

Voice-based AI development faces unique challenges in processing both linguistic and paralinguistic information. This study compares how large audio-language models (LALMs) and hum…

cs.CL2024

Large Language Models for Automated Literature Review: An Evaluation of Reference Generation, Abstract Writing, and Review Composition

Xuemei Tang, Xufeng Duan, Zhenguang G. Cai

Large language models (LLMs) have emerged as a potential solution to automate the complex processes involved in writing literature reviews, such as literature collection, organizat…