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Using Large Language Models (LLMs) to simulate user opinions has received growing attention. Yet LLMs, especially trained with reinforcement learning from human feedback (RLHF), are known to exhibit biases toward dominant viewpoints,…

Computation and Language · Computer Science 2025-12-09 Ziyun Yu , Yiru Zhou , Chen Zhao , Hongyi Wen

Advancements in Natural Language Processing (NLP), have led to the emergence of Large Language Models (LLMs) such as GPT, Llama, Claude, and Gemini, which excel across a range of tasks but require extensive fine-tuning to align their…

Computation and Language · Computer Science 2025-04-01 Angela Lopez-Cardona , Carlos Segura , Alexandros Karatzoglou , Sergi Abadal , Ioannis Arapakis

Large language models (LLMs) are proficient at generating fluent text with minimal task-specific supervision. Yet, their ability to provide well-grounded rationalizations for knowledge-intensive tasks remains under-explored. Such tasks,…

Computation and Language · Computer Science 2024-02-02 Aditi Mishra , Sajjadur Rahman , Hannah Kim , Kushan Mitra , Estevam Hruschka

Large Language Models (LLMs) are capable of displaying a wide range of abilities that are not directly connected with the task for which they are trained: predicting the next words of human-written texts. In this article, I review recent…

Artificial Intelligence · Computer Science 2023-12-19 Stefano Nolfi

Large language models (LLMs) offer emerging opportunities for psychological and behavioral research, but methodological guidance is lacking. This article provides a framework for using LLMs as psychological simulators across two primary…

Computers and Society · Computer Science 2026-04-07 Zhicheng Lin

Contemporary artificial intelligence research has been organized around two dominant ambitions: productivity, which treats AI systems as tools for accelerating work and economic output, and alignment, which focuses on ensuring that…

Artificial Intelligence · Computer Science 2026-03-10 W. Russell Neuman , Chad Coleman

Reinforcement Learning from Human Feedback (RLHF) is a pivotal technique for aligning large language models (LLMs) with human preferences, yet it is susceptible to reward overoptimization, in which policy models overfit to the reward model,…

Large language models (LLMs) have revolutionized many areas (e.g. natural language processing, software engineering, etc.) by achieving state-of-the-art performance on extensive downstream tasks. Aiming to achieve robust and general…

Artificial Intelligence · Computer Science 2024-01-18 Zhiming Li , Yushi Cao , Xiufeng Xu , Junzhe Jiang , Xu Liu , Yon Shin Teo , Shang-wei Lin , Yang Liu

In the rapidly evolving field of Large Language Models (LLMs), there is a critical need to thoroughly analyze their capabilities and risks. Central to our investigation are two novel elements. Firstly, it is the innovative parallels between…

Artificial Intelligence · Computer Science 2024-03-07 Jianqiiu Zhang

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

Computation and Language · Computer Science 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie

Reinforcement learning (RL) is a promising approach for aligning large language models (LLMs) knowledge with sequential decision-making tasks. However, few studies have thoroughly investigated the impact on LLM agents capabilities of…

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Language Agents (RPLAs). However, achieving authentic alignment…

Computation and Language · Computer Science 2026-04-20 Xintao Wang , Jian Yang , Weiyuan Li , Rui Xie , Jen-tse Huang , Jun Gao , Shuai Huang , Yueping Kang , Yuanli Gou , Hongwei Feng , Yanghua Xiao

General reasoning represents a long-standing and formidable challenge in artificial intelligence. Recent breakthroughs, exemplified by large language models (LLMs) and chain-of-thought prompting, have achieved considerable success on…

Computation and Language · Computer Science 2026-01-06 DeepSeek-AI , Daya Guo , Dejian Yang , Haowei Zhang , Junxiao Song , Peiyi Wang , Qihao Zhu , Runxin Xu , Ruoyu Zhang , Shirong Ma , Xiao Bi , Xiaokang Zhang , Xingkai Yu , Yu Wu , Z. F. Wu , Zhibin Gou , Zhihong Shao , Zhuoshu Li , Ziyi Gao , Aixin Liu , Bing Xue , Bingxuan Wang , Bochao Wu , Bei Feng , Chengda Lu , Chenggang Zhao , Chengqi Deng , Chenyu Zhang , Chong Ruan , Damai Dai , Deli Chen , Dongjie Ji , Erhang Li , Fangyun Lin , Fucong Dai , Fuli Luo , Guangbo Hao , Guanting Chen , Guowei Li , H. Zhang , Han Bao , Hanwei Xu , Haocheng Wang , Honghui Ding , Huajian Xin , Huazuo Gao , Hui Qu , Hui Li , Jianzhong Guo , Jiashi Li , Jiawei Wang , Jingchang Chen , Jingyang Yuan , Junjie Qiu , Junlong Li , J. L. Cai , Jiaqi Ni , Jian Liang , Jin Chen , Kai Dong , Kai Hu , Kaige Gao , Kang Guan , Kexin Huang , Kuai Yu , Lean Wang , Lecong Zhang , Liang Zhao , Litong Wang , Liyue Zhang , Lei Xu , Leyi Xia , Mingchuan Zhang , Minghua Zhang , Minghui Tang , Meng Li , Miaojun Wang , Mingming Li , Ning Tian , Panpan Huang , Peng Zhang , Qiancheng Wang , Qinyu Chen , Qiushi Du , Ruiqi Ge , Ruisong Zhang , Ruizhe Pan , Runji Wang , R. J. Chen , R. L. Jin , Ruyi Chen , Shanghao Lu , Shangyan Zhou , Shanhuang Chen , Shengfeng Ye , Shiyu Wang , Shuiping Yu , Shunfeng Zhou , Shuting Pan , S. S. Li , Shuang Zhou , Shaoqing Wu , Shengfeng Ye , Tao Yun , Tian Pei , Tianyu Sun , T. Wang , Wangding Zeng , Wanjia Zhao , Wen Liu , Wenfeng Liang , Wenjun Gao , Wenqin Yu , Wentao Zhang , W. L. Xiao , Wei An , Xiaodong Liu , Xiaohan Wang , Xiaokang Chen , Xiaotao Nie , Xin Cheng , Xin Liu , Xin Xie , Xingchao Liu , Xinyu Yang , Xinyuan Li , Xuecheng Su , Xuheng Lin , X. Q. Li , Xiangyue Jin , Xiaojin Shen , Xiaosha Chen , Xiaowen Sun , Xiaoxiang Wang , Xinnan Song , Xinyi Zhou , Xianzu Wang , Xinxia Shan , Y. K. Li , Y. Q. Wang , Y. X. Wei , Yang Zhang , Yanhong Xu , Yao Li , Yao Zhao , Yaofeng Sun , Yaohui Wang , Yi Yu , Yichao Zhang , Yifan Shi , Yiliang Xiong , Ying He , Yishi Piao , Yisong Wang , Yixuan Tan , Yiyang Ma , Yiyuan Liu , Yongqiang Guo , Yuan Ou , Yuduan Wang , Yue Gong , Yuheng Zou , Yujia He , Yunfan Xiong , Yuxiang Luo , Yuxiang You , Yuxuan Liu , Yuyang Zhou , Y. X. Zhu , Yanhong Xu , Yanping Huang , Yaohui Li , Yi Zheng , Yuchen Zhu , Yunxian Ma , Ying Tang , Yukun Zha , Yuting Yan , Z. Z. Ren , Zehui Ren , Zhangli Sha , Zhe Fu , Zhean Xu , Zhenda Xie , Zhengyan Zhang , Zhewen Hao , Zhicheng Ma , Zhigang Yan , Zhiyu Wu , Zihui Gu , Zijia Zhu , Zijun Liu , Zilin Li , Ziwei Xie , Ziyang Song , Zizheng Pan , Zhen Huang , Zhipeng Xu , Zhongyu Zhang , Zhen Zhang

The trustworthiness of Large Language Models (LLMs) refers to the extent to which their outputs are reliable, safe, and ethically aligned, and it has become a crucial consideration alongside their cognitive performance. In practice,…

Computation and Language · Computer Science 2024-12-24 Aaron J. Li , Satyapriya Krishna , Himabindu Lakkaraju

Recently, computer scientists have developed large language models (LLMs) by training prediction models with large-scale language corpora and human reinforcements. The LLMs have become one promising way to implement artificial intelligence…

Computers and Society · Computer Science 2023-08-22 Hyemin Han

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs,…

Computation and Language · Computer Science 2023-10-10 Thilo Hagendorff , Sarah Fabi

Large Language Models (LLMs) have emerged as dominant foundational models in modern NLP. However, the understanding of their prediction processes and internal mechanisms, such as feed-forward networks (FFN) and multi-head self-attention…

Computation and Language · Computer Science 2024-04-16 Xintong Wang , Xiaoyu Li , Xingshan Li , Chris Biemann

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

Artificial Intelligence · Computer Science 2025-07-08 Ruian Ke , Ruy M. Ribeiro

Large Language Models (LLMs) excel in generating personalized content and facilitating interactive dialogues, showcasing their remarkable aptitude for a myriad of applications. However, their capabilities in reasoning and providing…

Computation and Language · Computer Science 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang