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相关论文: Assessing and Understanding Creativity in Large La…

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Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Large Language Models (LLMs) are being applied to increasingly difficult problems and use cases. To navigate their vast solution spaces effectively, LLMs need to be creative. Yet the subjective nature of creativity and the limits of human…

Critiques are important for enhancing the performance of Large Language Models (LLMs), enabling both self-improvement and constructive feedback for others by identifying flaws and suggesting improvements. However, evaluating the critique…

计算与语言 · 计算机科学 2025-01-27 Zhengyang Tang , Ziniu Li , Zhenyang Xiao , Tian Ding , Ruoyu Sun , Benyou Wang , Dayiheng Liu , Fei Huang , Tianyu Liu , Bowen Yu , Junyang Lin

Evaluating creativity is challenging, even for humans, not only because of its subjectivity but also because it involves complex cognitive processes. Inspired by work in marketing, we attempt to break down visual advertisement creativity…

计算机视觉与模式识别 · 计算机科学 2025-09-24 Zhaoyi Joey Hou , Adriana Kovashka , Xiang Lorraine Li

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

Language models (LMs) have exhibited impressive abilities in generating codes from natural language requirements. In this work, we highlight the diversity of code generated by LMs as a critical criterion for evaluating their code generation…

软件工程 · 计算机科学 2024-08-28 Heejae Chon , Seonghyeon Lee , Jinyoung Yeo , Dongha Lee

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. Recent research has…

计算与语言 · 计算机科学 2024-12-05 Sergio E. Zanotto , Segun Aroyehun

The widespread adoption of Large Language Models (LLMs) and publicly available ChatGPT have marked a significant turning point in the integration of Artificial Intelligence (AI) into people's everyday lives. This study examines the ability…

计算与语言 · 计算机科学 2025-10-28 Sandeep Kumar , Tirthankar Ghosal , Vinayak Goyal , Asif Ekbal

Large Language Models (LLMs) have been widely used to support ideation in the writing process. However, whether generating ideas with the help of LLMs leads to idea fixation or idea expansion is unclear. This study examines how different…

人机交互 · 计算机科学 2025-05-06 Peinuan Qin , Chi-Lan Yang , Jingshu Li , Jing Wen , Yi-Chieh Lee

To advance the mathematical proficiency of large language models (LLMs), the DeepMath team has launched an open-source initiative aimed at developing an open mathematical LLM and systematically evaluating its mathematical creativity. This…

Large language models (LLM) have revolutionized the processing of natural language. Although first benchmarks of the process modeling abilities of LLM are promising, it is currently under debate to what extent an LLM can generate good…

计算与语言 · 计算机科学 2025-03-19 Peter Fettke , Constantin Houy

Large Language Models (LLMs) excel in code-related tasks like code generation, but benchmark evaluations often overlook task characteristics, such as difficulty. Moreover, benchmarks are usually built using tasks described with a single…

软件工程 · 计算机科学 2025-10-27 Florian Tambon , Amin Nikanjam , Cyrine Zid , Foutse Khomh , Giuliano Antoniol

The design and implementation of unit tests is a complex task many programmers neglect. This research evaluates the potential of Large Language Models (LLMs) in automatically generating test cases, comparing them with manual tests. An…

软件工程 · 计算机科学 2025-05-16 Martín Rodríguez , Gustavo Rossi , Alejandro Fernandez

The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text. As LLMs increasingly powerconversational agents used by the general…

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Measuring innovation often relies on context-specific proxies and on expert evaluation. Hence, empirical innovation research is often limited to settings where such data is available. We investigate how large language models (LLMs) can be…

计算与语言 · 计算机科学 2025-08-05 Robin Nowak , Patrick Figge , Carolin Haeussler

Large language models (LLMs) demonstrate increasing capabilities in creative text generation, yet systematic evaluations of their humor production remain underexplored. This study presents a comprehensive analysis of 13 state-of-the-art…

计算与语言 · 计算机科学 2025-04-07 Evgenii Evstafev

Reasoning based on Large Language Models (LLMs) has garnered increasing attention due to outstanding performance of these models in mathematical and complex logical tasks. Beginning with the Chain-of-Thought (CoT) prompting technique,…

人工智能 · 计算机科学 2025-11-27 Yuto Suzuki , Farnoush Banaei-Kashani

Large Language Models (LLMs) excel in generating personalized content and facilitating interactive dialogues, showcasing their remarkable aptitude for a myriad of applications. However, their capabilities in reasoning and providing…

计算与语言 · 计算机科学 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang

Recent advances in large language models (LLMs) have led to the development of various evaluation benchmarks. These benchmarks typically rely on a single instruction template for evaluating all LLMs on a specific task. In this paper, we…

计算与语言 · 计算机科学 2024-05-07 Moran Mizrahi , Guy Kaplan , Dan Malkin , Rotem Dror , Dafna Shahaf , Gabriel Stanovsky