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Large language models (LLMs) have recently demonstrated great success in generating and understanding natural language. While they have also shown potential beyond the domain of natural language, it remains an open question as to what…

计算与语言 · 计算机科学 2024-10-11 Muhammad Umair Nasir , Steven James , Julian Togelius

Developing full-stack web applications is complex and time-intensive, demanding proficiency across diverse technologies and frameworks. Although recent advances in multimodal large language models (MLLMs) enable automated webpage generation…

软件工程 · 计算机科学 2025-10-02 Yuxuan Wan , Tingshuo Liang , Jiakai Xu , Jingyu Xiao , Yintong Huo , Michael R. Lyu

Developing domain models is one of the few remaining places that require manual human labor in AI planning. Thus, in order to make planning more accessible, it is desirable to automate the process of domain model generation. To this end, we…

计算与语言 · 计算机科学 2024-05-14 James Oswald , Kavitha Srinivas , Harsha Kokel , Junkyu Lee , Michael Katz , Shirin Sohrabi

Large language models (LLMs) have achieved notable success in code generation. However, they still frequently produce uncompilable output because their next-token inference procedure does not model formal aspects of code. Although…

机器学习 · 计算机科学 2025-05-09 Niels Mündler , Jingxuan He , Hao Wang , Koushik Sen , Dawn Song , Martin Vechev

We introduce a simple approach that uses a large language model (LLM) to automatically implement a fully interpretable rule-based data-to-text system in pure Python. Experimental evaluation on the WebNLG dataset showed that such a…

计算与语言 · 计算机科学 2025-03-03 Jędrzej Warczyński , Mateusz Lango , Ondrej Dusek

Large language models (LLMs) excel at generating code from natural language (NL) descriptions. However, the plain textual descriptions are inherently ambiguous and often fail to capture complex requirements like intricate system behaviors,…

人工智能 · 计算机科学 2025-11-06 Wenxin Mao , Zhitao Wang , Long Wang , Sirong Chen , Cuiyun Gao , Luyang Cao , Ziming Liu , Qiming Zhang , Jun Zhou , Zhi Jin

Large Language Models (LLMs) have impacted the writing process, enhancing productivity by collaborating with humans in content creation platforms. However, generating high-quality, user-aligned text to satisfy real-world content creation…

计算与语言 · 计算机科学 2025-02-25 Yukyung Lee , Soonwon Ka , Bokyung Son , Pilsung Kang , Jaewook Kang

Advancements in large language models (LLMs) are revolutionizing interactive game design, enabling dynamic plotlines and interactions between players and non-player characters (NPCs). However, LLMs may exhibit flaws such as hallucinations,…

计算与语言 · 计算机科学 2025-02-25 Claire Jin , Sudha Rao , Xiangyu Peng , Portia Botchway , Jessica Quaye , Chris Brockett , Bill Dolan

Commit messages are crucial for documenting software changes, aiding in program comprehension and maintenance. However, creating effective commit messages is often overlooked by developers due to time constraints and varying levels of…

软件工程 · 计算机科学 2025-04-18 Varun Kumar Palakodeti , Abbas Heydarnoori

Recently, program synthesis driven by large language models (LLMs) has become increasingly popular. However, program synthesis for machine learning (ML) tasks still poses significant challenges. This paper explores a novel form of program…

Large Language Models (LLM) show strong abilities in code generation, but their skill in creating efficient parallel programs is less studied. This paper explores how LLMs generate task-based parallel code from three kinds of input prompts:…

编程语言 · 计算机科学 2026-02-27 Linus Bantel , Moritz Strack , Alexander Strack , Dirk Pflüger

Large Language Models (LLMs) have emerged as coding assistants, capable of generating source code from natural language prompts. With the increasing adoption of LLMs in software development, academic research and industry based projects are…

The efficiency of multi-agent systems driven by large language models (LLMs) largely hinges on their communication topology. However, designing an optimal topology is a non-trivial challenge, as it requires balancing competing objectives…

Large Language Models (LLMs) have shown incredible potential in code generation tasks, and recent research in prompt engineering have enhanced LLMs' understanding of textual information. However, ensuring the accuracy of generated code…

软件工程 · 计算机科学 2024-10-04 Haolin Jin , Zechao Sun , Huaming Chen

Code large language models have demonstrated remarkable capabilities in programming tasks, yet current benchmarks primarily focus on single modality rather than visual game development. Most existing code-related benchmarks evaluate syntax…

This paper presents an evaluation of three LLMs, GPT-4, Claude 3, and Gemini, for automated Behaviour-Driven Development (BDD) scenarios generation. To support this evaluation, we constructed a dataset of 500 user stories, requirement…

软件工程 · 计算机科学 2026-03-06 Amila Rathnayake , Mojtaba Shahin , Golnoush Abaei

Large Language Models (LLMs) have emerged as powerful tools for software development tasks such as code completion, translation, and optimization. However, their ability to generate efficient and correct code, particularly in complex…

分布式、并行与集群计算 · 计算机科学 2025-03-19 Bowen Cui , Tejas Ramesh , Oscar Hernandez , Keren Zhou

The development of architecture specifications is an initial and fundamental stage of the integrated circuit (IC) design process. Traditionally, architecture specifications are crafted by experienced chip architects, a process that is not…

硬件体系结构 · 计算机科学 2024-01-25 Mengming Li , Wenji Fang , Qijun Zhang , Zhiyao Xie

Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities relevant to Artificial General Intelligence. Recently, the…

Natural Language Description (NLD) is a Natural Language Processing (NLP) task that requires models to generate structured and meaningful outputs from natural language inputs. In this work, we propose NLD-LLM, a systematic NLP framework to…