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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) are increasingly used in robotics, especially for high-level action planning. Meanwhile, many robotics applications involve human supervisors or collaborators. Hence, it is crucial for LLMs to generate socially…

Robotics · Computer Science 2025-05-28 Lennart Wachowiak , Andrew Coles , Oya Celiktutan , Gerard Canal

Interpretability tools that offer explanations in the form of a dialogue have demonstrated their efficacy in enhancing users' understanding (Slack et al., 2023; Shen et al., 2023), as one-off explanations may fall short in providing…

Computation and Language · Computer Science 2024-04-25 Qianli Wang , Tatiana Anikina , Nils Feldhus , Josef van Genabith , Leonhard Hennig , Sebastian Möller

As the prevalence of mental health challenges, social media has emerged as a key platform for individuals to express their emotions.Deep learning tends to be a promising solution for analyzing mental health on social media. However, black…

Computation and Language · Computer Science 2024-10-15 Wei Zhai , Nan Bai , Qing Zhao , Jianqiang Li , Fan Wang , Hongzhi Qi , Meng Jiang , Xiaoqin Wang , Bing Xiang Yang , Guanghui Fu

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 , Michal Kosinski

Despite the many use cases for large language models (LLMs) in creating personalized chatbots, there has been limited research on evaluating the extent to which the behaviors of personalized LLMs accurately and consistently reflect specific…

Computation and Language · Computer Science 2024-04-03 Hang Jiang , Xiajie Zhang , Xubo Cao , Cynthia Breazeal , Deb Roy , Jad Kabbara

While large language models (LLMs), such as GPT-3, appear to be robust and general, their reasoning ability is not at a level to compete with the best models trained for specific natural language reasoning problems. In this study, we…

Computation and Language · Computer Science 2023-07-18 Zhun Yang , Adam Ishay , Joohyung Lee

Whether large language models (LLMs) process language similarly to humans has been the subject of much theoretical and practical debate. We examine this question through the lens of the production-interpretation distinction found in human…

Computation and Language · Computer Science 2025-06-04 Suet-Ying Lam , Qingcheng Zeng , Jingyi Wu , Rob Voigt

Generative large language models (LLMs) with instruct training such as GPT-4 can follow human-provided instruction prompts and generate human-like responses to these prompts. Apart from natural language responses, they have also been found…

Artificial Intelligence · Computer Science 2023-09-29 Sumit Kumar Jha , Susmit Jha , Patrick Lincoln , Nathaniel D. Bastian , Alvaro Velasquez , Rickard Ewetz , Sandeep Neema

This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics. Our examination involves a…

Computation and Language · Computer Science 2024-01-25 Jie Tian , Jixin Hou , Zihao Wu , Peng Shu , Zhengliang Liu , Yujie Xiang , Beikang Gu , Nicholas Filla , Yiwei Li , Ning Liu , Xianyan Chen , Keke Tang , Tianming Liu , Xianqiao Wang

With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting and discriminatory content, reflect incorrect social values,…

Computation and Language · Computer Science 2023-04-21 Hao Sun , Zhexin Zhang , Jiawen Deng , Jiale Cheng , Minlie Huang

The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infer others' beliefs, intentions, and emotions from text. Given that LLMs are trained on language…

Computation and Language · Computer Science 2026-03-20 Anna Babarczy , Andras Lukacs , Peter Vedres , Zeteny Bujka

As the capabilities of large language models (LLMs) continue to advance, evaluating their performance becomes increasingly crucial and challenging. This paper aims to bridge this gap by introducing CMMLU, a comprehensive Chinese benchmark…

Computation and Language · Computer Science 2024-01-19 Haonan Li , Yixuan Zhang , Fajri Koto , Yifei Yang , Hai Zhao , Yeyun Gong , Nan Duan , Timothy Baldwin

There has been recent interest in whether large language models (LLMs) can introspect about their own internal states. Such abilities would make LLMs more interpretable, and also validate the use of standard introspective methods in…

Computation and Language · Computer Science 2025-09-25 Siyuan Song , Jennifer Hu , Kyle Mahowald

Large Language Models (LLMs) are known for their remarkable ability to generate synthesized 'knowledge', such as text documents, music, images, etc. However, there is a huge gap between LLM's and human capabilities for understanding…

Computation and Language · Computer Science 2024-08-14 Vladimir Cherkassky , Eng Hock Lee

Lexical iconicity, a direct relation between a word's meaning and its form, is an important aspect of every natural language, most commonly manifesting through sound-meaning associations. Since Large language models' (LLMs') access to both…

Computation and Language · Computer Science 2025-10-17 Anna Marklová , Jiří Milička , Leonid Ryvkin , Ľudmila Lacková Bennet , Libuše Kormaníková

Large language models (LLMs) have shown the potential to be integrated into human daily lives. Therefore, user preference is the most critical criterion for assessing LLMs' performance in real-world scenarios. However, existing benchmarks…

Computation and Language · Computer Science 2023-07-28 Liang Xu , Anqi Li , Lei Zhu , Hang Xue , Changtai Zhu , Kangkang Zhao , Haonan He , Xuanwei Zhang , Qiyue Kang , Zhenzhong Lan

This work explores the capability of conversational chatbots powered by large language models (LLMs), to understand and characterize predicate symmetry, a cognitive linguistic function traditionally believed to be an inherent human trait.…

Computation and Language · Computer Science 2024-07-09 Daniela N. Rim , Heeyoul Choi

Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level machine translation (MT) as a testbed, this paper provides…

Computation and Language · Computer Science 2023-10-25 Longyue Wang , Chenyang Lyu , Tianbo Ji , Zhirui Zhang , Dian Yu , Shuming Shi , Zhaopeng Tu

Large language models (LLMs) such as ChatGPT and Vicuna have shown remarkable capacities in comprehending and producing language. However, their internal workings remain a black box, and it is unclear whether LLMs and chatbots can develop…

Computation and Language · Computer Science 2024-03-27 Zhenguang G. Cai , Xufeng Duan , David A. Haslett , Shuqi Wang , Martin J. Pickering