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Recent breakthroughs in Large Language Models (LLMs) have led to a qualitative leap in artificial intelligence' s performance on reasoning tasks, particularly demonstrating remarkable capabilities in mathematical, symbolic, and commonsense…

Training Large Language Models (LLMs) to follow user instructions has been shown to supply the LLM with ample capacity to converse fluently while being aligned with humans. Yet, it is not completely clear how an LLM can lead a plan-grounded…

计算与语言 · 计算机科学 2024-02-05 Diogo Glória-Silva , Rafael Ferreira , Diogo Tavares , David Semedo , João Magalhães

Evaluating large language models (LLMs) in long-form, knowledge-grounded role-play dialogues remains challenging. This study compares LLM-generated and human-authored responses in multi-turn professional training simulations through human…

计算与语言 · 计算机科学 2025-10-10 Dongxu Lu , Johan Jeuring , Albert Gatt

Formal models of games help us account for and predict behavior, leading to more robust and innovative designs. While the games research community has proposed many formalisms for both the "game half" (game models, game description…

编程语言 · 计算机科学 2017-03-17 Chris Martens , Matthew A. Hammer

Large language models (LLMs) excel at complex reasoning tasks such as mathematics and coding, yet they frequently struggle with simple interactive tasks that young children perform effortlessly. This discrepancy highlights a critical gap…

人工智能 · 计算机科学 2025-09-01 Yi Liao , Yu Gu , Yuan Sui , Zining Zhu , Yifan Lu , Guohua Tang , Zhongqian Sun , Wei Yang

Large Language Models (LLMs) are increasingly applied to automate software engineering tasks, including the generation of UML class diagrams from natural language descriptions. While prior work demonstrates that LLMs can produce…

软件工程 · 计算机科学 2026-04-07 Rabia Iftikhar , Andreas Rausch

Large language models have the potential to be valuable in the healthcare industry, but it's crucial to verify their safety and effectiveness through rigorous evaluation. For this purpose, we comprehensively evaluated both open-source LLMs…

计算与语言 · 计算机科学 2024-02-13 Ankit Pal , Malaikannan Sankarasubbu

Can we leverage LLMs to model the process of discovering novel language model (LM) architectures? Inspired by real research, we propose a multi-agent LLM approach that simulates the conventional stages of research, from ideation and…

人工智能 · 计算机科学 2025-06-26 Junyan Cheng , Peter Clark , Kyle Richardson

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…

人工智能 · 计算机科学 2023-12-13 Caoyun Fan , Jindou Chen , Yaohui Jin , Hao He

The large language model (LLM) based agents have demonstrated their capacity to automate and expedite software development processes. In this paper, we focus on game development and propose a multi-agent collaborative framework, dubbed…

人工智能 · 计算机科学 2025-09-09 Dake Chen , Haoyang Zhang , Hanbin Wang , Yunhao Huo , Yuzhao Li , Junjie Wang

The prototyping of computer games, particularly card games, requires extensive human effort in creative ideation and gameplay evaluation. Recent advances in Large Language Models (LLMs) offer opportunities to automate and streamline these…

计算与语言 · 计算机科学 2025-09-10 Danrui Li , Sen Zhang , Sam S. Sohn , Kaidong Hu , Muhammad Usman , Mubbasir Kapadia

Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on human-authored problems, even solving some competitive-programming problems. Self-play has proven useful in games such as Go, and thus it is…

机器学习 · 计算机科学 2023-04-13 Patrick Haluptzok , Matthew Bowers , Adam Tauman Kalai

Creatively translating complex gameplay ideas into executable artifacts (e.g., games as Unity projects and code) remains a central challenge in computational game creativity. Gameplay design patterns provide a structured representation for…

人工智能 · 计算机科学 2026-05-01 Hugh Xuechen Liu , Kıvanç Tatar

Large Language Models (LLMs) have demonstrated superior performance in language understanding benchmarks. CALM, a popular approach, leverages linguistic priors of LLMs -- GPT-2 -- for action candidate recommendations to improve the…

计算与语言 · 计算机科学 2023-11-15 Arjun Vaithilingam Sudhakar , Prasanna Parthasarathi , Janarthanan Rajendran , Sarath Chandar

Real-world AI systems are tackling increasingly complex problems, often through interactions among large language model (LLM) agents. When these agents develop inconsistent conventions, coordination can break down. Applications such as…

人工智能 · 计算机科学 2025-12-29 Ryan Zhang , Herbert Woisetschläger

Recently, various studies have leveraged Large Language Models (LLMs) to help decision-making and planning in environments, and try to align the LLMs' knowledge with the world conditions. Nonetheless, the capacity of LLMs to continuously…

机器学习 · 计算机科学 2023-10-16 Yicheng Feng , Yuxuan Wang , Jiazheng Liu , Sipeng Zheng , Zongqing Lu

Game development is a highly specialized task that relies on a complex game engine powered by complex programming languages, preventing many gaming enthusiasts from handling it. This paper introduces the Chat Game Engine (ChatGE) powered by…

人工智能 · 计算机科学 2024-12-17 Jiale Hong , Hongqiu Wu , Hai Zhao

Design assistants are frameworks, tools or applications intended to facilitate both the creative and technical facets of design processes. Large language models (LLMs) are AI systems engineered to analyze and produce text resembling human…

人机交互 · 计算机科学 2025-02-12 Swaroop Panda

As generative artificial intelligence advances, Large Language Models (LLMs) are being explored for automated graphical user interface (GUI) design. This study investigates the usability and adaptability of LLM-generated interfaces by…

人机交互 · 计算机科学 2026-02-02 Bartosz Sawicki , Tomasz Les , Dariusz Parzych , Aleksandra Wycisk-Ficek , Pawel Trebacz , Pawel Zawadzki

Large language models (LLMs) are increasingly explored as general-purpose reasoners, particularly in agentic contexts. However, their outputs remain prone to mathematical and logical errors. This is especially challenging in open-ended…

人工智能 · 计算机科学 2025-05-30 Agnieszka Mensfelt , Kostas Stathis , Vince Trencsenyi