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相关论文: On the Creativity of Large Language Models

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Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. Unlike conventional models, LLMs can adapt to new domains through prompt…

人工智能 · 计算机科学 2024-06-18 Ming Cheung

Large language models appear quite creative, often performing on par with the average human on creative tasks. However, research on LLM creativity has focused solely on \textit{products}, with little attention on the creative…

人机交互 · 计算机科学 2024-06-07 Surabhi S. Nath , Peter Dayan , Claire Stevenson

With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scientific method. LLMs are now involved in experimental design,…

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

计算与语言 · 计算机科学 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality. Even more recently, LLMs have been extended into…

计算与语言 · 计算机科学 2024-04-03 Kilian Carolan , Laura Fennelly , Alan F. Smeaton

Recent advancements in large language models (LLMs) have sparked optimism about their potential to accelerate scientific discovery, with a growing number of works proposing research agents that autonomously generate and validate new ideas.…

计算与语言 · 计算机科学 2024-09-09 Chenglei Si , Diyi Yang , Tatsunori Hashimoto

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

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with…

计算与语言 · 计算机科学 2024-09-26 Zeyneb N. Kaya , Souvick Ghosh

The potential for Large Language Models (LLMs) to generate new information offers a potential step change for research and innovation. This is challenging to assert as it can be difficult to determine what an LLM has previously seen during…

计算与语言 · 计算机科学 2024-05-24 Thomas Greatrix , Roger Whitaker , Liam Turner , Walter Colombo

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we…

Natural language processing based on large language models (LLMs) is a booming field of AI research. After neural networks have proven to outperform humans in games and practical domains based on pattern recognition, we might stand now at a…

计算机与社会 · 计算机科学 2023-03-31 Anna Strasser

The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in some areas. However, this focus often neglects whether…

计算与语言 · 计算机科学 2025-07-29 Yanzhu Guo , Guokan Shang , Chloé Clavel

Generative AI has demonstrated unprecedented creativity in the field of computer vision, yet such phenomena have not been observed in natural language processing. In particular, large language models (LLMs) can hardly produce written works…

计算与语言 · 计算机科学 2024-06-18 Jing Chen , Xinyu Zhu , Cheng Yang , Chufan Shi , Yadong Xi , Yuxiang Zhang , Junjie Wang , Jiashu Pu , Rongsheng Zhang , Yujiu Yang , Tian Feng

Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works…

计算与语言 · 计算机科学 2024-10-18 Humza Naveed , Asad Ullah Khan , Shi Qiu , Muhammad Saqib , Saeed Anwar , Muhammad Usman , Naveed Akhtar , Nick Barnes , Ajmal Mian

Interpretable machine learning has exploded as an area of interest over the last decade, sparked by the rise of increasingly large datasets and deep neural networks. Simultaneously, large language models (LLMs) have demonstrated remarkable…

计算与语言 · 计算机科学 2024-02-06 Chandan Singh , Jeevana Priya Inala , Michel Galley , Rich Caruana , Jianfeng Gao

Creativity is a fundamental aspect of intelligence, involving the ability to generate novel and appropriate solutions across diverse contexts. While Large Language Models (LLMs) have been extensively evaluated for their creative…

计算机视觉与模式识别 · 计算机科学 2025-03-20 Xinyu Fang , Zhijian Chen , Kai Lan , Lixin Ma , Shengyuan Ding , Yingji Liang , Xiangyu Zhao , Farong Wen , Zicheng Zhang , Guofeng Zhang , Haodong Duan , Kai Chen , Dahua Lin

Creativity is often seen as a hallmark of human intelligence. While large language models (LLMs) are increasingly perceived as generating creative text, there is still no holistic and scalable framework to evaluate their creativity across…

Large Language Models (LLMs) have emerged as transformative tools in artificial intelligence (AI), exhibiting remarkable capabilities across diverse tasks such as text generation, reasoning, and decision-making. While their success has…

Large Language Models (LLMs) have revolutionized natural language processing but can exhibit biases and may generate toxic content. While alignment techniques like Reinforcement Learning from Human Feedback (RLHF) reduce these issues, their…

计算与语言 · 计算机科学 2024-06-11 Behnam Mohammadi

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

机器学习 · 计算机科学 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique