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Related papers: Standards for Belief Representations in LLMs

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Large language models (LLMs) are increasingly employed in information-seeking and decision-making tasks. Despite their broad utility, LLMs tend to generate information that conflicts with real-world facts, and their persuasive style can…

Computation and Language · Computer Science 2024-09-19 Arslan Chaudhry , Sridhar Thiagarajan , Dilan Gorur

As large language models (LLMs) are increasingly used in human-centered tasks, assessing their psychological traits is crucial for understanding their social impact and ensuring trustworthy AI alignment. While existing reviews have covered…

Computers and Society · Computer Science 2025-05-02 Wenhan Dong , Yuemeng Zhao , Zhen Sun , Yule Liu , Zifan Peng , Jingyi Zheng , Zongmin Zhang , Ziyi Zhang , Jun Wu , Ruiming Wang , Shengmin Xu , Xinyi Huang , Xinlei He

Large Language Models (LLMs) are increasingly employed in various question-answering tasks. However, recent studies showcase that LLMs are susceptible to persuasion and could adopt counterfactual beliefs. We present a systematic evaluation…

Computation and Language · Computer Science 2026-03-20 Fan Huang , Haewoon Kwak , Jisun An

Large language models (LLMs) have shown considerable potential in supporting medical diagnosis. However, their effective integration into clinical workflows is hindered by physicians' difficulties in perceiving and trusting LLM…

Human-Computer Interaction · Computer Science 2026-01-28 Yuansong Xu , Yichao Zhu , Haokai Wang , Yuchen Wu , Yang Ouyang , Hanlu Li , Wenzhe Zhou , Xinyu Liu , Chang Jiang , Quan Li

From pre-trained language model (PLM) to large language model (LLM), the field of natural language processing (NLP) has witnessed steep performance gains and wide practical uses. The evaluation of a research field guides its direction of…

Computation and Language · Computer Science 2023-08-16 Ziyu Zhuang , Qiguang Chen , Longxuan Ma , Mingda Li , Yi Han , Yushan Qian , Haopeng Bai , Zixian Feng , Weinan Zhang , Ting Liu

Decisions by Machine Learning (ML) models have become ubiquitous. Trusting these decisions requires understanding how algorithms take them. Hence interpretability methods for ML are an active focus of research. A central problem in this…

Machine Learning · Computer Science 2019-01-25 Philipp Schmidt , Felix Biessmann

While Large Language Models (LLMs) are fundamentally next-token prediction systems, their practical applications extend far beyond this basic function. From natural language processing and text generation to conversational assistants and…

Computation and Language · Computer Science 2025-03-10 Vishakha Agrawal , Archie Chaudhury , Shreya Agrawal

Large language models (LLMs) are increasingly used in applications requiring factual accuracy, yet their outputs often contain hallucinated responses. While fact-checking can mitigate these errors, existing methods typically retrieve…

Computation and Language · Computer Science 2026-01-07 Haoran Wang , Maryam Khalid , Qiong Wu , Jian Gao , Cheng Cao

The model editing problem concerns how language models should learn new facts about the world over time. While empirical research on model editing has drawn widespread attention, the conceptual foundations of model editing remain shaky --…

Computation and Language · Computer Science 2024-06-28 Peter Hase , Thomas Hofweber , Xiang Zhou , Elias Stengel-Eskin , Mohit Bansal

Using Large Language Models (LLMs) for Process Mining (PM) tasks is becoming increasingly essential, and initial approaches yield promising results. However, little attention has been given to developing strategies for evaluating and…

Databases · Computer Science 2024-07-01 Alessandro Berti , Humam Kourani , Hannes Hafke , Chiao-Yun Li , Daniel Schuster

Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit intermediate reasoning steps and key tokens that serve as…

Computation and Language · Computer Science 2023-11-08 Sree Harsha Tanneru , Chirag Agarwal , Himabindu Lakkaraju

Large Language Models (LLMs) are increasingly employed in software engineering tasks such as requirements elicitation, design, and evaluation, raising critical questions regarding their alignment with human judgments on responsible AI…

Software Engineering · Computer Science 2025-11-07 Asma Yamani , Malak Baslyman , Moataz Ahmed

Large language models (LLMs) increasingly help people solve problems, from debugging code to repairing machinery. This process requires generating plausible hypotheses from partial descriptions, then updating them as more information…

Machine Learning · Computer Science 2026-05-08 Hua-Dong Xiong

Large Language Models (LLMs) are increasingly used in settings where reliable self-assessment is critical. Assessing model reliability has evolved from using probabilistic correctness estimates to, more recently, eliciting verbalized…

Computation and Language · Computer Science 2026-05-11 Sree Bhattacharyya , Samarth Khanna , Leona Chen , Lucas Craig , Tharun Dilliraj , James Z. Wang

Large language models (LLMs) increasingly support heterogeneous tasks within a single interface, requiring users to form, update, and act upon beliefs about one system across domains with different reliability profiles. Understanding how…

Human-Computer Interaction · Computer Science 2026-02-03 Shreyan Biswas , Alexander Erlei , Ujwal Gadiraju

Large language models (LLMs) are increasingly tasked with strategic decision-making under incomplete information, such as in negotiation and policymaking. While LLMs can excel at many such tasks, they also fail in ways that are poorly…

Computation and Language · Computer Science 2026-05-04 Jan Sobotka , Mustafa O. Karabag , Ufuk Topcu

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Computation and Language · Computer Science 2024-01-01 Yupeng Chang , Xu Wang , Jindong Wang , Yuan Wu , Linyi Yang , Kaijie Zhu , Hao Chen , Xiaoyuan Yi , Cunxiang Wang , Yidong Wang , Wei Ye , Yue Zhang , Yi Chang , Philip S. Yu , Qiang Yang , Xing Xie

As LLMs grow more powerful, their most profound achievement may be recognising when to say "I don't know". Existing studies on LLM self-knowledge have been largely constrained by human-defined notions of feasibility, often neglecting the…

Computation and Language · Computer Science 2025-09-16 Sahil Kale , Vijaykant Nadadur

Large Language Models (LLMs) demonstrate remarkable performance in semantic understanding and generation, yet accurately assessing their output reliability remains a significant challenge. While numerous studies have explored calibration…

Artificial Intelligence · Computer Science 2024-12-18 Liangru Xie , Hui Liu , Jingying Zeng , Xianfeng Tang , Yan Han , Chen Luo , Jing Huang , Zhen Li , Suhang Wang , Qi He

Large language models (LLMs) are increasingly used as judges of chain-of-thought (CoT) reasoning, but it remains unclear whether they can reliably assess process faithfulness rather than just answer plausibility. We introduce C2-Faith, a…

Computation and Language · Computer Science 2026-03-06 Avni Mittal , Rauno Arike
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