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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

Large Language Models (LLMs) struggle to directly generate correct plans for complex multi-constraint planning problems, even with self-verification and self-critique. For example, a U.S. domestic travel planning benchmark TravelPlanner was…

Artificial Intelligence · Computer Science 2025-01-30 Yilun Hao , Yongchao Chen , Yang Zhang , Chuchu Fan

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

Artificial Intelligence · Computer Science 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Inspired by the recent success of large language models (LLMs) like ChatGPT, researchers start to explore the adoption of LLMs for agile hardware design, such as generating design RTL based on natural-language instructions. However, in…

Machine Learning · Computer Science 2023-11-14 Yao Lu , Shang Liu , Qijun Zhang , Zhiyao Xie

Large Language Models (LLMs) reasoning abilities are increasingly being applied to classical board and card games, but the dominant approach -- involving prompting for direct move generation -- has significant drawbacks. It relies on the…

Large-scale task planning is a major challenge. Recent work exploits large language models (LLMs) directly as a policy and shows surprisingly interesting results. This paper shows that LLMs provide a commonsense model of the world in…

Robotics · Computer Science 2023-10-31 Zirui Zhao , Wee Sun Lee , David Hsu

Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic. While starting as a niche area within natural language processing, LLMs have shown remarkable…

Computation and Language · Computer Science 2024-12-10 Roberto Gallotta , Graham Todd , Marvin Zammit , Sam Earle , Antonios Liapis , Julian Togelius , Georgios N. Yannakakis

There is a growing literature on reasoning by large language models (LLMs), but the discussion on the uncertainty in their responses is still lacking. Our aim is to assess the extent of confidence that LLMs have in their answers and how it…

Computation and Language · Computer Science 2024-12-23 Yudi Pawitan , Chris Holmes

Large Language Models (LLMs) have seen great advance in both academia and industry, and their popularity results in numerous open-source frameworks and techniques in accelerating LLM pre-training, fine-tuning, and inference. Training and…

Performance · Computer Science 2023-12-04 Longteng Zhang , Xiang Liu , Zeyu Li , Xinglin Pan , Peijie Dong , Ruibo Fan , Rui Guo , Xin Wang , Qiong Luo , Shaohuai Shi , Xiaowen Chu

Generative artificial intelligence (Generative AI), and in particular Large Language Models (LLMs) have gained significant popularity among researchers and industrial communities, paving the way for integrating LLMs in different domains,…

Computer Science and Game Theory · Computer Science 2024-10-15 Alonso Silva

Large Language Models (LLMs) have significantly advanced natural language processing, demonstrating exceptional reasoning, tool usage, and memory capabilities. As their applications expand into multi-agent environments, there arises a need…

Computation and Language · Computer Science 2024-11-28 Lin Xu , Zhiyuan Hu , Daquan Zhou , Hongyu Ren , Zhen Dong , Kurt Keutzer , See Kiong Ng , Jiashi Feng

Large Language Models (LLMs) have shown remarkable capabilities as autonomous agents, yet existing benchmarks either focus on single-agent tasks or are confined to narrow domains, failing to capture the dynamics of multi-agent coordination…

Multiagent Systems · Computer Science 2025-03-05 Kunlun Zhu , Hongyi Du , Zhaochen Hong , Xiaocheng Yang , Shuyi Guo , Zhe Wang , Zhenhailong Wang , Cheng Qian , Xiangru Tang , Heng Ji , Jiaxuan You

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…

Computation and Language · Computer Science 2026-01-07 Ine Gevers , Walter Daelemans

The resurgence and rapid advancement of Generative Artificial Intelligence (GenAI) in 2023 has catalyzed transformative shifts across numerous industry sectors, including urban transportation and logistics. This study investigates the…

Artificial Intelligence · Computer Science 2024-09-24 Shaowei Ying , Zhenlong Li , Manzhu Yu

Routing large language models (LLMs) is a new paradigm that uses a router to recommend the best LLM from a pool of candidates for a given input. In this paper, our comprehensive analysis with more than 8,500 LLMs reveals a novel model-level…

Computation and Language · Computer Science 2025-05-21 Zhongzhan Huang , Guoming Ling , Yupei Lin , Yandong Chen , Shanshan Zhong , Hefeng Wu , Liang Lin

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

Computation and Language · Computer Science 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

Recently developed large language models (LLMs) have been shown to perform remarkably well on a wide range of language understanding tasks. But, can they really "reason" over the natural language? This question has been receiving…

Computation and Language · Computer Science 2024-06-07 Mihir Parmar , Nisarg Patel , Neeraj Varshney , Mutsumi Nakamura , Man Luo , Santosh Mashetty , Arindam Mitra , Chitta Baral

Large language models (LLMs), especially generative pre-trained transformers (GPTs), have recently demonstrated outstanding ability in information comprehension and problem-solving. This has motivated many studies in applying LLMs to…

Machine Learning · Computer Science 2024-05-21 Han Zhang , Akram Bin Sediq , Ali Afana , Melike Erol-Kantarci

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

Large language models (LLMs) have achieved remarkable success in natural language processing (NLP), demonstrating significant capabilities in processing and understanding text data. However, recent studies have identified limitations in…

Artificial Intelligence · Computer Science 2025-02-18 Qiming Wu , Zichen Chen , Will Corcoran , Misha Sra , Ambuj K. Singh