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Related papers: BeHonest: Benchmarking Honesty in Large Language M…

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Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to faithfully express their knowledge. Despite promising, current…

Computation and Language · Computer Science 2024-09-30 Siheng Li , Cheng Yang , Taiqiang Wu , Chufan Shi , Yuji Zhang , Xinyu Zhu , Zesen Cheng , Deng Cai , Mo Yu , Lemao Liu , Jie Zhou , Yujiu Yang , Ngai Wong , Xixin Wu , Wai Lam

As large language models (LLMs) become more capable and agentic, the requirement for trust in their outputs grows significantly, yet at the same time concerns have been mounting that models may learn to lie in pursuit of their goals. To…

Large Language Models (LLMs) have achieved remarkable success across various industries due to their exceptional generative capabilities. However, for safe and effective real-world deployments, ensuring honesty and helpfulness is critical.…

Computation and Language · Computer Science 2024-12-12 Chujie Gao , Siyuan Wu , Yue Huang , Dongping Chen , Qihui Zhang , Zhengyan Fu , Yao Wan , Lichao Sun , Xiangliang Zhang

Recent research has made significant strides in aligning large language models (LLMs) with helpfulness and harmlessness. In this paper, we argue for the importance of alignment for \emph{honesty}, ensuring that LLMs proactively refuse to…

Computation and Language · Computer Science 2024-10-29 Yuqing Yang , Ethan Chern , Xipeng Qiu , Graham Neubig , Pengfei Liu

Recent research on large language models (LLMs) has demonstrated their ability to understand and employ deceptive behavior, even without explicit prompting. However, such behavior has only been observed in rare, specialized cases and has…

Computation and Language · Computer Science 2025-06-24 Laurène Vaugrante , Francesca Carlon , Maluna Menke , Thilo Hagendorff

The rapid progress in Large Language Models (LLMs) could transform many fields, but their fast development creates significant challenges for oversight, ethical creation, and building user trust. This comprehensive review looks at key trust…

Computers and Society · Computer Science 2024-07-22 Md Meftahul Ferdaus , Mahdi Abdelguerfi , Elias Ioup , Kendall N. Niles , Ken Pathak , Steven Sloan

This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack the…

Computers and Society · Computer Science 2025-05-05 Junfeng Jiao , Saleh Afroogh , Abhejay Murali , Kevin Chen , David Atkinson , Amit Dhurandhar

People tell lies when seeking rewards. Large language models (LLMs) are aligned to human values with reinforcement learning where they get rewards if they satisfy human preference. We find that this also induces dishonesty in helpful and…

Computation and Language · Computer Science 2024-06-06 Youcheng Huang , Jingkun Tang , Duanyu Feng , Zheng Zhang , Wenqiang Lei , Jiancheng Lv , Anthony G. Cohn

Ensuring alignment, which refers to making models behave in accordance with human intentions [1,2], has become a critical task before deploying large language models (LLMs) in real-world applications. For instance, OpenAI devoted six months…

Artificial Intelligence · Computer Science 2024-03-22 Yang Liu , Yuanshun Yao , Jean-Francois Ton , Xiaoying Zhang , Ruocheng Guo , Hao Cheng , Yegor Klochkov , Muhammad Faaiz Taufiq , Hang Li

Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream…

Computation and Language · Computer Science 2024-02-22 Yingji Li , Mengnan Du , Rui Song , Xin Wang , Ying Wang

Large Language Models (LLMs) have demonstrated an alarming ability to impersonate humans in conversation, raising concerns about their potential misuse in scams and deception. Humans have a right to know if they are conversing to an LLM. We…

Computation and Language · Computer Science 2024-12-23 Gilad Gressel , Rahul Pankajakshan , Yisroel Mirsky

Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities,…

Artificial Intelligence · Computer Science 2025-09-19 Zhilun Zhou , Jing Yi Wang , Nicholas Sukiennik , Chen Gao , Fengli Xu , Yong Li , James Evans

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these…

Computation and Language · Computer Science 2025-07-08 Jianchao Ji , Yutong Chen , Mingyu Jin , Wujiang Xu , Wenyue Hua , Yongfeng Zhang

The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many researchers to propose their own LLM benchmarks. Noticing preliminary…

Artificial Intelligence · Computer Science 2025-05-15 Timothy R. McIntosh , Teo Susnjak , Nalin Arachchilage , Tong Liu , Paul Watters , Malka N. Halgamuge

Recently Multimodal Large Language Models (MLLMs) have achieved considerable advancements in vision-language tasks, yet produce potentially harmful or untrustworthy content. Despite substantial work investigating the trustworthiness of…

Artificial Intelligence · Computer Science 2026-01-14 Yanxu Zhu , Shitong Duan , Xiangxu Zhang , Jitao Sang , Peng Zhang , Tun Lu , Xiao Zhou , Jing Yao , Xiaoyuan Yi , Xing Xie

Large Language Models (LLMs) have demonstrated remarkable success across various domains but often lack fairness considerations, potentially leading to discriminatory outcomes against marginalized populations. Unlike fairness in traditional…

Computation and Language · Computer Science 2024-08-09 Thang Doan Viet , Zichong Wang , Minh Nhat Nguyen , Wenbin Zhang

Large language models (LLMs), such as ChatGPT, have rapidly penetrated into people's work and daily lives over the past few years, due to their extraordinary conversational skills and intelligence. ChatGPT has become the fastest-growing…

Computation and Language · Computer Science 2024-09-04 Wenxuan Wang

Recent advancements in Large Language Models (LLMs) have significantly enhanced interactions between users and models. These advancements concurrently underscore the need for rigorous safety evaluations due to the manifestation of social…

Computation and Language · Computer Science 2025-03-26 Dahyun Jung , Seungyoon Lee , Hyeonseok Moon , Chanjun Park , Heuiseok Lim

Large language models (LLMs) are capable of generating plausible explanations of how they arrived at an answer to a question. However, these explanations can misrepresent the model's "reasoning" process, i.e., they can be unfaithful. This,…

Computation and Language · Computer Science 2025-05-21 Katie Matton , Robert Osazuwa Ness , John Guttag , Emre Kıcıman

Previous research has shown that LLMs finetuned on malicious or incorrect completions within narrow domains (e.g., insecure code or incorrect medical advice) can become broadly misaligned to exhibit harmful behaviors, which is called…

Computation and Language · Computer Science 2026-01-21 Xuhao Hu , Peng Wang , Xiaoya Lu , Dongrui Liu , Xuanjing Huang , Jing Shao
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