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Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities,…

人工智能 · 计算机科学 2025-09-19 Zhilun Zhou , Jing Yi Wang , Nicholas Sukiennik , Chen Gao , Fengli Xu , Yong Li , James Evans

Large Language Models (LLMs) have demonstrated their remarkable capabilities in numerous fields. This survey focuses on how LLMs empower users, regardless of their technical background, to use human languages to automatically generate…

软件工程 · 计算机科学 2025-04-03 Nam Huynh , Beiyu Lin

An essential element of human mathematical reasoning is our number sense -- an abstract understanding of numbers and their relationships -- which allows us to solve problems involving vast number spaces using limited computational…

人工智能 · 计算机科学 2025-04-02 Roussel Rahman

Large Language Models (LLMs) have gained prominence in the AI landscape due to their exceptional performance. Thus, it is essential to gain a better understanding of their capabilities and limitations, among others in terms of nonmonotonic…

人工智能 · 计算机科学 2024-10-17 Ilias Tachmazidis , Sotiris Batsakis , Grigoris Antoniou

Competitive programming platforms like LeetCode, Codeforces, and HackerRank evaluate programming skills, often used by recruiters for screening. With the rise of advanced Large Language Models (LLMs) such as ChatGPT, Gemini, and Meta AI,…

软件工程 · 计算机科学 2024-09-10 Md Mustakim Billah , Palash Ranjan Roy , Zadia Codabux , Banani Roy

Large Language Models (LLMs) have demonstrated notable capabilities across various tasks, showcasing complex problem-solving abilities. Understanding and executing complex rules, along with multi-step planning, are fundamental to logical…

人工智能 · 计算机科学 2024-10-15 Jiayi Gui , Yiming Liu , Jiale Cheng , Xiaotao Gu , Xiao Liu , Hongning Wang , Yuxiao Dong , Jie Tang , Minlie Huang

Large Language Models (LLMs) have been widely used to automate programming tasks. Their capabilities have been evaluated by assessing the quality of generated code through tests or proofs. The extent to which they can reason about code is a…

软件工程 · 计算机科学 2026-04-08 Changshu Liu , Yang Chen , Reyhaneh Jabbarvand

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Large language models (LLMs) have achieved striking successes on many benchmarks, yet recent studies continue to expose fundamental weaknesses. In this paper, we introduce Concept, a simple word-guessing board game, as a benchmark for…

计算与语言 · 计算机科学 2026-01-07 Ine Gevers , Walter Daelemans

Large language models (LLMs) regularly demonstrate new and impressive performance on a wide range of language, knowledge, and reasoning benchmarks. Such rapid progress has led many commentators to argue that LLM general cognitive…

计算与语言 · 计算机科学 2025-02-21 James Fodor

Although large language models (LLMs) have shown exceptional capabilities across a wide range of tasks, reliable evaluation remains a critical challenge due to data contamination, opaque operation, and subjective preferences. To address…

Decision-making is a complex process requiring diverse abilities, making it an excellent framework for evaluating Large Language Models (LLMs). Researchers have examined LLMs' decision-making through the lens of Game Theory. However,…

Advancing planning and reasoning capabilities of Large Language Models (LLMs) is one of the key prerequisites towards unlocking their potential for performing reliably in complex and impactful domains. In this paper, we aim to demonstrate…

The rise of Large Reasoning Models (LRMs) signifies a paradigm shift toward advanced computational reasoning. Yet, this progress disrupts traditional agent frameworks, traditionally anchored by execution-oriented Large Language Models…

Strategic reasoning enables agents to cooperate, communicate, and compete with other agents in diverse situations. Existing approaches to solving strategic games rely on extensive training, yielding strategies that do not generalize to new…

人工智能 · 计算机科学 2023-05-31 Kanishk Gandhi , Dorsa Sadigh , Noah D. Goodman

Large Language Models (LLMs) are highly proficient in language-based tasks. Their language capabilities have positioned them at the forefront of the future AGI (Artificial General Intelligence) race. However, on closer inspection, Valmeekam…

计算与语言 · 计算机科学 2025-03-17 Dibyanayan Bandyopadhyay , Soham Bhattacharjee , Asif Ekbal

Recent advances in reasoning with large language models (LLMs) have demonstrated strong performance on complex mathematical tasks, including combinatorial optimization. Techniques such as Chain-of-Thought and In-Context Learning have…

人工智能 · 计算机科学 2025-09-17 Marylou Fauchard , Florian Carichon , Margarida Carvalho , Golnoosh Farnadi

This paper investigates the ability of large language models (LLMs) to solve statistical tasks, as well as their capacity to assess the quality of reasoning. While state-of-the-art LLMs have demonstrated remarkable performance in a range of…

计算与语言 · 计算机科学 2026-01-22 Crish Nagarkar , Leonid Bogachev , Serge Sharoff

It has been established in recent work that Large Language Models (LLMs) can be prompted to "self-play" conversational games that probe certain capabilities (general instruction following, strategic goal orientation, language understanding…

计算与语言 · 计算机科学 2024-06-03 Anne Beyer , Kranti Chalamalasetti , Sherzod Hakimov , Brielen Madureira , Philipp Sadler , David Schlangen

Large language models (LLMs) have demonstrated significant potential to accelerate scientific discovery as valuable tools for analyzing data, generating hypotheses, and supporting innovative approaches in various scientific fields. In this…

计算与语言 · 计算机科学 2025-10-30 Jin Huang , Silviu Cucerzan , Sujay Kumar Jauhar , Ryen W. White