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The development of highly fluent large language models (LLMs) has prompted increased interest in assessing their reasoning and problem-solving capabilities. We investigate whether several LLMs can solve a classic type of deductive reasoning…

Computation and Language · Computer Science 2024-04-16 Spencer M. Seals , Valerie L. Shalin

The effective assessment of the instruction-following ability of large language models (LLMs) is of paramount importance. A model that cannot adhere to human instructions might be not able to provide reliable and helpful responses. In…

Computation and Language · Computer Science 2023-11-17 Yimin Jing , Renren Jin , Jiahao Hu , Huishi Qiu , Xiaohua Wang , Peng Wang , Deyi Xiong

Large language models (LLMs), such as GPT series and Llama series have demonstrated strong capabilities in natural language processing, contextual understanding, and text generation. In recent years, researchers are trying to enhance the…

Computation and Language · Computer Science 2024-10-08 Ziyang Chen , Stylios Moscholios

Large Language Models (LLMs) and pre-trained Language Models (LMs) have achieved impressive success on many software engineering tasks (e.g., code completion and code generation). By leveraging huge existing code corpora (e.g., GitHub),…

Software Engineering · Computer Science 2025-01-16 Xin Yin , Chao Ni , Xiaodan Xu , Xinrui Li , Xiaohu Yang

Effective collaboration requires groups to strategically regulate themselves to overcome challenges. Research has shown that groups may fail to regulate due to differences in members' perceptions of challenges which may benefit from…

Computation and Language · Computer Science 2024-01-04 Wannapon Suraworachet , Jennifer Seon , Mutlu Cukurova

Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated exceptional performance in various natural language processing tasks and have shown the ability to solve certain reasoning problems. However, their reasoning…

Artificial Intelligence · Computer Science 2023-07-18 Adam Ishay , Zhun Yang , Joohyung Lee

Large Language Models (LLMs) have been touted as AI models possessing advanced reasoning abilities. However, recent works have shown that LLMs often bypass true reasoning using shortcuts, sparking skepticism. To study the reasoning…

Artificial Intelligence · Computer Science 2024-10-24 Rishi Hazra , Gabriele Venturato , Pedro Zuidberg Dos Martires , Luc De Raedt

Large Language Models (LLMs) have shown remarkable performance in various natural language processing tasks but face challenges in mathematical reasoning, where complex problem-solving requires both linguistic understanding and mathematical…

Computation and Language · Computer Science 2025-03-20 Shuguang Chen , Guang Lin

This paper introduces a novel approach to Dialogue State Tracking (DST) that leverages Large Language Models (LLMs) to generate natural language descriptions of dialogue states, moving beyond traditional slot-value representations.…

Computation and Language · Computer Science 2025-03-13 Rafael Carranza , Mateo Alejandro Rojas

This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to operate within formally specified, rule-governed environments. We evaluate four LLMs (Gemini 2.5 Pro and…

Artificial Intelligence · Computer Science 2026-02-24 Maciej Świechowski , Adam Żychowski , Jacek Mańdziuk

Large Language Models (LLMs) are a powerful technology that augment human skill to create new opportunities, akin to the development of steam engines and the internet. However, LLMs come with a high cost. They require significant computing…

Computers and Society · Computer Science 2024-04-16 Vishwas Sathish , Hannah Lin , Aditya K Kamath , Anish Nyayachavadi

Large language models (LLMs) can carry out human-like dialogue, but unlike humans, they are stateless due to the superposition property. However, during multi-turn, multi-agent interactions, LLMs begin to exhibit consistent, character-like…

Computation and Language · Computer Science 2026-04-14 Siqi Fan , Xiusheng Huang , Yiqun Yao , Xuezhi Fang , Kang Liu , Peng Han , Shuo Shang , Aixin Sun , Yequan Wang

Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions:…

Computation and Language · Computer Science 2024-06-17 Wenhao Zhu , Hongyi Liu , Qingxiu Dong , Jingjing Xu , Shujian Huang , Lingpeng Kong , Jiajun Chen , Lei Li

Despite the fact that large language models (LLMs) show exceptional skill in instruction following tasks, this strength can turn into a vulnerability when the models are required to disregard certain instructions. Instruction-following…

Computation and Language · Computer Science 2025-08-12 Yerin Hwang , Yongil Kim , Jahyun Koo , Taegwan Kang , Hyunkyung Bae , Kyomin Jung

Large language models (LLMs) are capable of performing conditional sequence generation tasks, such as translation or summarization, through instruction fine-tuning. The fine-tuning data is generally sequentially concatenated from a specific…

Computation and Language · Computer Science 2023-08-24 Yijin Liu , Xianfeng Zeng , Fandong Meng , Jie Zhou

Large language models (LLMs) have demonstrated remarkable performances on a wide range of natural language tasks. Yet, LLMs' successes have been largely restricted to tasks concerning words, sentences, or documents, and it remains…

Computation and Language · Computer Science 2024-07-24 Andrew Shin , Kunitake Kaneko

Pre-trained large language models (PLMs) underlie most new developments in natural language processing. They have shifted the field from application-specific model pipelines to a single model that is adapted to a wide range of tasks.…

Computation and Language · Computer Science 2023-06-30 Joshua Maynez , Priyanka Agrawal , Sebastian Gehrmann

Large language models (LLMs) have led to a series of breakthroughs in natural language processing (NLP), owing to their excellent understanding and generation abilities. Remarkably, what further sets these models apart is the massive…

Computation and Language · Computer Science 2022-11-10 Daliang Li , Ankit Singh Rawat , Manzil Zaheer , Xin Wang , Michal Lukasik , Andreas Veit , Felix Yu , Sanjiv Kumar

Large language models (LLMs) demonstrate impressive capabilities in mathematical reasoning. However, despite these achievements, current evaluations are mostly limited to specific mathematical topics, and it remains unclear whether LLMs are…

Computation and Language · Computer Science 2025-04-01 Arash Gholami Davoodi , Seyed Pouyan Mousavi Davoudi , Pouya Pezeshkpour

We investigate the predictability of large language model (LLM) capabilities: given records of past experiments using different model families, numbers of parameters, tasks, and numbers of in-context examples, can we accurately predict LLM…

Computation and Language · Computer Science 2023-11-01 Qinyuan Ye , Harvey Yiyun Fu , Xiang Ren , Robin Jia