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We introduce LLM CHESS, an evaluation framework designed to probe the generalization of reasoning and instruction-following abilities in large language models (LLMs) through extended agentic interaction in the domain of chess. We rank over…

Artificial Intelligence · Computer Science 2025-12-02 Sai Kolasani , Maxim Saplin , Nicholas Crispino , Kyle Montgomery , Jared Quincy Davis , Matei Zaharia , Chi Wang , Chenguang Wang

Game theory, as an analytical tool, is frequently utilized to analyze human behavior in social science research. With the high alignment between the behavior of Large Language Models (LLMs) and humans, a promising research direction is to…

Artificial Intelligence · Computer Science 2023-12-13 Caoyun Fan , Jindou Chen , Yaohui Jin , Hao He

Large Language Models (LLMs) harness extensive data from the Internet, storing a broad spectrum of prior knowledge. While LLMs have proven beneficial as decision-making aids, their reliability is hampered by limitations in reasoning,…

Artificial Intelligence · Computer Science 2024-03-12 Hongyi Guo , Zhihan Liu , Yufeng Zhang , Zhaoran Wang

Collectible card games (CCGs) are a difficult genre for AI due to their partial observability, long-term decision-making, and evolving card sets. Due to this, current AI models perform vastly worse than human players at CCG tasks such as…

Artificial Intelligence · Computer Science 2025-08-13 Timo Bertram

This report documents the development, test, and application of Large Language Models (LLMs) for automated text analysis, with a specific focus on gambling-like elements in digital games, such as lootboxes. The project aimed not only to…

General Economics · Economics 2024-12-13 Thomas Krause , Steffen Otterbach , Johannes Singer

Implementing board games in code can be a time-consuming task. However, Large Language Models (LLMs) have been proven effective at generating code for domain-specific tasks with simple contextual information. We aim to investigate whether…

Large Language Models' (LLMs) programming capabilities enable their participation in open-source games: a game-theoretic setting in which players submit computer programs in lieu of actions. These programs offer numerous advantages,…

Computer Science and Game Theory · Computer Science 2025-12-02 Swadesh Sistla , Max Kleiman-Weiner

Large language models (LLMs) have achieved impressive performance on many natural language processing tasks. However, their capabilities on graph-structured data remain relatively unexplored. In this paper, we conduct a series of…

Machine Learning · Computer Science 2023-10-10 Yuntong Hu , Zheng Zhang , Liang Zhao

The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry. But despite the surge in interest in this rapidly evolving area, there are scarce…

Artificial Intelligence · Computer Science 2024-03-18 Xinrun Xu , Yuxin Wang , Chaoyi Xu , Ziluo Ding , Jiechuan Jiang , Zhiming Ding , Börje F. Karlsson

Large Language Models (LLMs) are powerful tools, capable of leveraging their training on natural language to write stories, generate code, and answer questions. But can they generate functional video game levels? Game levels, with their…

Artificial Intelligence · Computer Science 2023-06-02 Graham Todd , Sam Earle , Muhammad Umair Nasir , Michael Cerny Green , Julian Togelius

Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary for complex games with incomplete information remains a…

Computation and Language · Computer Science 2025-04-16 Meiling Tao , Xuechen Liang , Xinyuan Song , Yangfan He , Yiling Tao , Jianhui Wang , Sun Li Tianyu Shi

This paper investigates the utilization of Large Language Models (LLMs) for solving complex linguistic puzzles, a domain requiring advanced reasoning and adept translation capabilities akin to human cognitive processes. We explore specific…

Computation and Language · Computer Science 2025-02-04 Zheng-Lin Lin , Yu-Fei Shih , Shu-Kai Hsieh

Large language models (LLMs) have demonstrated significant potential in the realm of natural language understanding and programming code processing tasks. Their capacity to comprehend and generate human-like code has spurred research into…

Software Engineering · Computer Science 2024-03-07 Chongzhou Fang , Ning Miao , Shaurya Srivastav , Jialin Liu , Ruoyu Zhang , Ruijie Fang , Asmita , Ryan Tsang , Najmeh Nazari , Han Wang , Houman Homayoun

Large Language Models (LLMs) have been increasingly used in real-world settings, yet their strategic decision-making abilities remain largely unexplored. To fully benefit from the potential of LLMs, it's essential to understand their…

Artificial Intelligence · Computer Science 2024-10-16 Nathan Herr , Fernando Acero , Roberta Raileanu , María Pérez-Ortiz , Zhibin Li

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

We investigate whether large language models (LLMs) can predict whether they will succeed on a given task and whether their predictions improve as they progress through multi-step tasks. We also investigate whether LLMs can learn from…

Computation and Language · Computer Science 2026-01-01 Casey O. Barkan , Sid Black , Oliver Sourbut

Playing board games is considered a major challenge for both humans and AI researchers. Because some complicated board games are quite hard to learn, humans usually begin with playing on smaller boards and incrementally advance to master…

Machine Learning · Computer Science 2021-07-20 Shai Ben-Assayag , Ran El-Yaniv

Chess provides an ideal testbed for evaluating the reasoning, modeling, and abstraction capabilities of large language models (LLMs), as it has well-defined structure and objective ground truth while admitting a wide spectrum of skill…

Machine Learning · Computer Science 2025-10-29 Qianfeng Wen , Zhenwei Tang , Ashton Anderson

To some, the advent of artificial intelligence (AI) promises better decision-making and increased military effectiveness while reducing the influence of human error and emotions. However, there is still debate about how AI systems,…

Computers and Society · Computer Science 2024-10-04 Max Lamparth , Anthony Corso , Jacob Ganz , Oriana Skylar Mastro , Jacquelyn Schneider , Harold Trinkunas

This paper presents a comprehensive evaluation of the performance of state-of-the-art Large Language Models (LLMs) on challenging university-level algorithms exams. By testing multiple models on both a Romanian exam and its high-quality…

Computation and Language · Computer Science 2025-06-06 Adrian Marius Dumitran , Theodor-Pierre Moroianu , Vasile Paul Alexe