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Humor is a fundamental facet of human cognition and interaction. Yet, despite recent advances in natural language processing, humor detection remains a challenging task that is complicated by the scarcity of datasets that pair humorous…

计算与语言 · 计算机科学 2024-06-24 Zachary Horvitz , Jingru Chen , Rahul Aditya , Harshvardhan Srivastava , Robert West , Zhou Yu , Kathleen McKeown

The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many researchers to propose their own LLM benchmarks. Noticing preliminary…

人工智能 · 计算机科学 2025-05-15 Timothy R. McIntosh , Teo Susnjak , Nalin Arachchilage , Tong Liu , Paul Watters , Malka N. Halgamuge

Humor understanding is an important and challenging research in natural language processing. As the popularity of pre-trained language models (PLMs), some recent work makes preliminary attempts to adopt PLMs for humor recognition and…

计算与语言 · 计算机科学 2024-07-08 Yuyan Chen , Zhixu Li , Jiaqing Liang , Yanghua Xiao , Bang Liu , Yunwen Chen

Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor. However, the understanding of puns in large language models (LLMs) has not been…

计算与语言 · 计算机科学 2024-06-18 Zhijun Xu , Siyu Yuan , Lingjie Chen , Deqing Yang

Humor is a broad and complex form of communication that remains challenging for machines. Despite its broadness, most existing research on computational humor traditionally focused on modeling a specific type of humor. In this work, we wish…

计算与语言 · 计算机科学 2025-08-28 Mor Turgeman , Chen Shani , Dafna Shahaf

Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities,…

人工智能 · 计算机科学 2025-09-19 Zhilun Zhou , Jing Yi Wang , Nicholas Sukiennik , Chen Gao , Fengli Xu , Yong Li , James Evans

With the release of ChatGPT and other large language models (LLMs) the discussion about the intelligence, possibilities, and risks, of current and future models have seen large attention. This discussion included much debated scenarios…

人工智能 · 计算机科学 2024-07-31 Nils Körber , Silvan Wehrli , Christopher Irrgang

Humour, as a complex language form, is derived from myriad aspects of life. Whilst existing work on computational humour has focussed almost exclusively on short pun-based jokes, we investigate whether the ability of Large Language Models…

计算与语言 · 计算机科学 2025-09-15 Tyler Loakman , William Thorne , Chenghua Lin

Can a machine understand the meanings of natural language? Recent developments in the generative large language models (LLMs) of artificial intelligence have led to the belief that traditional philosophical assumptions about machine…

计算与语言 · 计算机科学 2023-10-27 Vladimír Havlík

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…

Computational humor is a frontier for creating advanced and engaging natural language processing (NLP) applications, such as sophisticated dialogue systems. While previous studies have benchmarked the humor capabilities of Large Language…

计算与语言 · 计算机科学 2025-11-17 Ritsu Sakabe , Hwichan Kim , Tosho Hirasawa , Mamoru Komachi

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

计算与语言 · 计算机科学 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

As Large Language Models (LLMs) are increasingly deployed as social agents and trained to produce humor and irony, a question emerges: when encountering witty AI remarks, do people interpret these as intentional communication or mere…

计算与语言 · 计算机科学 2025-10-21 Xiaohui Rao , Hanlin Wu , Zhenguang G. Cai

Comedy serves as a profound reflection of the times we live in and is a staple element of human interactions. In light of the widespread adoption of Large Language Models (LLMs), the intersection of humor and AI has become no laughing…

计算与语言 · 计算机科学 2025-11-25 Adrianna Romanowski , Pedro H. V. Valois , Kazuhiro Fukui

Current Large Language Models (LLMs) are unparalleled in their ability to generate grammatically correct, fluent text. LLMs are appearing rapidly, and debates on LLM capacities have taken off, but reflection is lagging behind. Thus, in this…

计算与语言 · 计算机科学 2023-11-01 Bram M. A. van Dijk , Tom Kouwenhoven , Marco R. Spruit , Max J. van Duijn

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(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

计算与语言 · 计算机科学 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

Thanks to rapid progress in artificial intelligence, we have entered an era when technology and philosophy intersect in interesting ways. Sitting squarely at the centre of this intersection are large language models (LLMs). The more adept…

计算与语言 · 计算机科学 2023-02-17 Murray Shanahan

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI)…

Large Language Models (LLMs) have shown significant limitations in understanding creative content, as demonstrated by Hessel et al. (2023)'s influential work on the New Yorker Cartoon Caption Contest (NYCCC). Their study exposed a…

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