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The advent of Large Language Models (LLMs) has significantly transformed tasks across Software Engineering. In the context of Business Process Management, LLMs are now being explored as tools to derive process models directly from textual…

Software Engineering · Computer Science 2026-05-01 Pedro-Aarón Hernández-Ávalos , Luciano García-Bañuelos

While large language models (LLMs) have demonstrated impressive performance in question-answering tasks, their performance is limited when the questions require knowledge that is not included in the model's training data and can only be…

Computation and Language · Computer Science 2023-09-22 Abhigya Sodani , Lauren Moos , Matthew Mirman

Large Language Models (LLMs) are important tools for reasoning and problem-solving, while they often operate passively, answering questions without actively discovering new ones. This limitation reduces their ability to simulate human-like…

Computational Engineering, Finance, and Science · Computer Science 2025-09-26 Hong Su

The emergence of Large Language Models (LLMs) have fundamentally altered the way we interact with digital systems and have led to the pursuit of LLM powered AI agents to assist in daily workflows. LLMs, whilst powerful and capable of…

Computation and Language · Computer Science 2024-08-05 Prattyush Mangal , Carol Mak , Theo Kanakis , Timothy Donovan , Dave Braines , Edward Pyzer-Knapp

Large Language Models (LLMs) have demonstrated remarkable proficiency in understanding text and generating high-quality responses. However, a critical distinction from human cognition is their typical lack of a distinct internal `reading'…

Computation and Language · Computer Science 2025-07-08 Yuanxin Wang , Ganesh Venkatesh

Although Large Language Models (LLMs) have demonstrated impressive formal reasoning abilities, they often break down when problems require complex proof planning. One promising approach for improving LLM reasoning abilities involves…

Artificial Intelligence · Computer Science 2026-01-27 Joseph Cotnareanu , Didier Chetelat , Yingxue Zhang , Mark Coates

Reasoning-enhanced large language models (LLMs) explicitly generate intermediate reasoning steps prior to generating final answers, helping the model excel in complex problem-solving. In this paper, we demonstrate that this emerging…

Machine Learning · Computer Science 2025-05-22 Tong Wu , Chong Xiang , Jiachen T. Wang , G. Edward Suh , Prateek Mittal

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

Computation and Language · Computer Science 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

Large Language Models (LLMs) have shown human-like reasoning abilities but still struggle with complex logical problems. This paper introduces a novel framework, Logic-LM, which integrates LLMs with symbolic solvers to improve logical…

Computation and Language · Computer Science 2023-10-20 Liangming Pan , Alon Albalak , Xinyi Wang , William Yang Wang

Research on emergent patterns in Large Language Models (LLMs) has gained significant traction in both psychology and artificial intelligence, motivating the need for a comprehensive review that offers a synthesis of this complex landscape.…

Computation and Language · Computer Science 2024-12-23 Zhisheng Tang , Mayank Kejriwal

Large Language Models (LLMs) have demonstrated impressive reasoning abilities through test-time computation (TTC) techniques such as chain-of-thought prompting and tree-based reasoning. However, we argue that current reasoning LLMs (RLLMs)…

Computation and Language · Computer Science 2025-05-27 Jiahao Lu , Ziwei Xu , Mohan Kankanhalli

Large language models (LLMs) are a promising venue for natural language understanding and generation. However, current LLMs are far from reliable: they are prone to generating non-factual information and, more crucially, to contradicting…

Computation and Language · Computer Science 2024-09-24 Diego Calanzone , Stefano Teso , Antonio Vergari

Large language models (LLMs) have demonstrated outstanding performance across various tasks, yet they still exhibit limitations such as hallucination, unfaithful reasoning, and toxic content. One potential approach to mitigate these issues…

Computation and Language · Computer Science 2024-07-19 Yuxuan Yao , Han Wu , Zhijiang Guo , Biyan Zhou , Jiahui Gao , Sichun Luo , Hanxu Hou , Xiaojin Fu , Linqi Song

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

Machine Learning · Computer Science 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

Human reasoning involves different strategies, each suited to specific problems. Prior work shows that large language model (LLMs) tend to favor a single reasoning strategy, potentially limiting their effectiveness in diverse reasoning…

Computation and Language · Computer Science 2025-07-17 Yanjian Zhang , Guillaume Wisniewski , Nadi Tomeh , Thierry Charnois

Recent advancements in the reasoning skills of Large Language Models (LLMs) demonstrate an increase in the ability of LLMs to solve simple planning tasks. However, as long as the driving force behind improved reasoning capability is the…

Artificial Intelligence · Computer Science 2025-02-03 Andrey Borro , Patricia J Riddle , Michael W Barley , Michael J Witbrock

Large language models (LLMs) are transforming society, powering applications from smartphone assistants to autonomous driving. Yet cloud-based LLM services alone cannot serve a growing class of applications, including those operating under…

Signal Processing · Electrical Eng. & Systems 2026-05-12 Liangqi Yuan , Wenzhi Fang , Shiqiang Wang , H. Vincent Poor , Christopher G. Brinton

Cognitive Reframing, a core element of Cognitive Behavioral Therapy (CBT), helps individuals reinterpret negative experiences by finding positive meaning. Recent advances in Large Language Models (LLMs) have demonstrated improved…

Computation and Language · Computer Science 2025-04-02 Yilin Qi , Dong Won Lee , Cynthia Breazeal , Hae Won Park

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 ability of Large Language Models (LLMs) to perform reasoning tasks such as deduction has been widely investigated in recent years. Yet, their capacity to generate proofs-faithful, human-readable explanations of why conclusions…

Artificial Intelligence · Computer Science 2026-01-21 Hui Yang , Jiaoyan Chen , Uli Sattler
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