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Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Language Models (LLMs) can answer questions, write high-quality…

Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations emphasize problem-solving accuracy, overlooking the fragmented…

Computation and Language · Computer Science 2026-05-12 Conrad Borchers , Jill-Jênn Vie , Roger Azevedo

Advances in Large Language Models (LLMs) have sparked interest in their ability to solve Olympiad-level math problems. However, the training and evaluation of these models are constrained by the limited size and quality of available…

Computation and Language · Computer Science 2025-06-30 Sadegh Mahdavi , Muchen Li , Kaiwen Liu , Christos Thrampoulidis , Leonid Sigal , Renjie Liao

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Topic modelling, as a well-established unsupervised technique, has found extensive use in automatically detecting significant topics within a corpus of documents. However, classic topic modelling approaches (e.g., LDA) have certain…

Computation and Language · Computer Science 2024-03-27 Yida Mu , Chun Dong , Kalina Bontcheva , Xingyi Song

While state-of-the-art large language models (LLMs) demonstrate advanced reasoning capabilities-achieving remarkable performance on challenging competitive math and coding benchmarks-they also frequently fail on tasks that are easy for…

Computation and Language · Computer Science 2025-07-11 Alan Malek , Jiawei Ge , Nevena Lazic , Chi Jin , András György , Csaba Szepesvári

There is increasing interest in employing large language models (LLMs) as cognitive models. For such purposes, it is central to understand which properties of human cognition are well-modeled by LLMs, and which are not. In this work, we…

Large Language Models (LLMs) have emerged as transformative tools in artificial intelligence (AI), exhibiting remarkable capabilities across diverse tasks such as text generation, reasoning, and decision-making. While their success has…

Socratic questioning is an educational method that allows students to discover answers to complex problems by asking them a series of thoughtful questions. Generation of didactically sound questions is challenging, requiring understanding…

Computation and Language · Computer Science 2022-11-24 Kumar Shridhar , Jakub Macina , Mennatallah El-Assady , Tanmay Sinha , Manu Kapur , Mrinmaya Sachan

While large language models (LLMs) challenge conventional methods of teaching and learning, they present an exciting opportunity to improve efficiency and scale high-quality instruction. One promising application is the generation of…

Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series. In these lectures, written for readers with a background in mathematics or…

Computation and Language · Computer Science 2023-10-09 Michael R. Douglas

Large Language Models (LLMs) have shown excellent performance in language understanding, text generation, code synthesis, and many other tasks, while they still struggle in complex multi-step reasoning problems, such as mathematical…

Computation and Language · Computer Science 2024-06-05 Haolong Li , Yu Ma , Yinqi Zhang , Chen Ye , Jie Chen

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

Human-Computer Interaction · Computer Science 2024-04-10 M. Namvarpour , A. Razi

Large Language Models (LLMs) represent a leap in artificial intelligence, excelling in tasks using human language(s). Although the main focus of general-purpose LLMs is not code generation, they have shown promising results in the domain.…

Software Engineering · Computer Science 2024-01-30 Sanka Rasnayaka , Guanlin Wang , Ridwan Shariffdeen , Ganesh Neelakanta Iyer

Large Language Models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused on code writing tasks, but there is now a shift in importance…

Human-Computer Interaction · Computer Science 2023-11-13 Paul Denny , Juho Leinonen , James Prather , Andrew Luxton-Reilly , Thezyrie Amarouche , Brett A. Becker , Brent N. Reeves

We introduce modeLing, a novel benchmark of Linguistics Olympiad-style puzzles which tests few-shot reasoning in AI systems. Solving these puzzles necessitates inferring aspects of a language's grammatical structure from a small number of…

Computation and Language · Computer Science 2024-06-26 Nathan A. Chi , Teodor Malchev , Riley Kong , Ryan A. Chi , Lucas Huang , Ethan A. Chi , R. Thomas McCoy , Dragomir Radev

Large Language Models (LLMs) have made significant progress in reasoning, demonstrating their capability to generate human-like responses. This study analyzes the problem-solving capabilities of LLMs in the domain of thermodynamics. A…

Computational Engineering, Finance, and Science · Computer Science 2025-12-18 Rebecca Loubet , Pascal Zittlau , Luisa Vollmer , Marco Hoffmann , Sophie Fellenz , Fabian Jirasek , Heike Leitte , Hans Hasse

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

Large language models (LLMs) excel at solving problems with clear and complete statements, but often struggle with nuanced environments or interactive tasks which are common in most real-world scenarios. This highlights the critical need…

While systems designed for solving planning tasks vastly outperform Large Language Models (LLMs) in this domain, they usually discard the rich semantic information embedded within task descriptions. In contrast, LLMs possess parametrised…

Computation and Language · Computer Science 2025-02-03 Andrey Borro , Patricia J Riddle , Michael W Barley , Michael J Witbrock