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In this paper, we explore the generation of one-liner jokes through multi-step reasoning. Our work involved reconstructing the process behind creating humorous one-liners and developing a working prototype for humor generation. We conducted…

计算与语言 · 计算机科学 2024-05-14 Alexey Tikhonov , Pavel Shtykovskiy

Language is the principal tool for human communication, in which humor is one of the most attractive parts. Producing natural language like humans using computers, a.k.a, Natural Language Generation (NLG), has been widely used for dialogue…

计算与语言 · 计算机科学 2022-07-05 Benyou Wang , Xiangbo Wu , Xiaokang Liu , Jianquan Li , Prayag Tiwari , Qianqian Xie

Creative plot generation presents a fundamental challenge for language models: transforming a concise premise into a coherent narrative that sustains global structure, character development, and emotional resonance. Although recent Large…

计算与语言 · 计算机科学 2026-03-18 Abhinav Thorat , Ravi Kolla , Jyotin Goel , Niranjan Pedanekar

Cross-domain analogical reasoning is a core creative ability that can be challenging for humans. Recent work has shown some proofs-of concept of Large language Models' (LLMs) ability to generate cross-domain analogies. However, the…

计算与语言 · 计算机科学 2023-06-05 Zijian Ding , Arvind Srinivasan , Stephen MacNeil , Joel Chan

Large Language Models (LLMs) have revolutionized natural language processing through their state of art reasoning capabilities. This paper explores the convergence of LLM reasoning techniques and feature generation for machine learning…

计算与语言 · 计算机科学 2025-03-21 Dharani Chandra

Emotion estimation in images is a challenging task, typically using computer vision methods to directly estimate people's emotions using face, body pose and contextual cues. In this paper, we explore whether Large Language Models (LLMs) can…

计算机视觉与模式识别 · 计算机科学 2023-09-26 Vera Yang , Archita Srivastava , Yasaman Etesam , Chuxuan Zhang , Angelica Lim

Humor, deeply rooted in societal meanings and cultural details, poses a unique challenge for machines. While advances have been made in natural language processing, real-world humor often thrives in a multi-modal context, encapsulated…

计算机视觉与模式识别 · 计算机科学 2025-06-12 Yuyan Chen , Songzhou Yan , Zhihong Zhu , Zhixu Li , Yanghua Xiao

Generating humor and quotes are very challenging problems in the field of computational linguistics and are often tackled separately. In this paper, we present a controlled Long Short-Term Memory (LSTM) architecture which is trained with…

计算与语言 · 计算机科学 2018-06-14 Bhargav Chippada , Shubajit Saha

The use of Large Language Models (LLMs) has become ubiquitous, with abundant applications in computational creativity. One such application is fictional story generation. Fiction is a narrative that occurs in a story world that is slightly…

计算与语言 · 计算机科学 2024-08-16 Aisha Khatun , Daniel G. Brown

The evaluation of machine-generated image captions is a complex and evolving challenge. With the advent of Multimodal Large Language Models (MLLMs), image captioning has become a core task, increasing the need for robust and reliable…

计算机视觉与模式识别 · 计算机科学 2025-06-02 Sara Sarto , Marcella Cornia , Rita Cucchiara

In modern dialogue systems, the use of Large Language Models (LLMs) has grown exponentially due to their capacity to generate diverse, relevant, and creative responses. Despite their strengths, striking a balance between the LLMs'…

计算与语言 · 计算机科学 2023-08-01 Chen Zhang

Multimodal large language models (MLLMs) excel at generating highly detailed captions but often produce hallucinations. Our analysis reveals that existing hallucination detection methods struggle with detailed captions. We attribute this to…

计算机视觉与模式识别 · 计算机科学 2025-07-08 Saehyung Lee , Seunghyun Yoon , Trung Bui , Jing Shi , Sungroh Yoon

Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this field. However, the prevalent approach used in text generation,…

计算与语言 · 计算机科学 2024-08-12 Nicolo Micheletti , Samuel Belkadi , Lifeng Han , Goran Nenadic

The recent surge of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities. This idea has sparked a blend of excitement and apprehension. However, a critical piece that has…

Large Language Models have become popular for their remarkable capabilities in human-oriented tasks and traditional natural language processing tasks. Its efficient functioning is attributed to the attention mechanism in the Transformer…

计算与语言 · 计算机科学 2023-06-06 Ritwik Sinha , Zhao Song , Tianyi Zhou

Neural architecture search (NAS) traditionally requires significant human expertise or automated trial-and-error to design deep learning models. We present NN-Caption, an LLM-guided neural architecture search pipeline that generates…

机器学习 · 计算机科学 2025-12-18 Krunal Jesani , Dmitry Ignatov , Radu Timofte

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

Humor is a central aspect of human communication that has not been solved for artificial agents so far. Large language models (LLMs) are increasingly able to capture implicit and contextual information. Especially, OpenAI's ChatGPT recently…

人工智能 · 计算机科学 2023-06-08 Sophie Jentzsch , Kristian Kersting

This study presents a theory-inspired visual narrative generative system that integrates conceptual principles-comic authoring idioms-with generative and language models to enhance the comic creation process. Our system combines human…

人工智能 · 计算机科学 2024-09-27 Yi-Chun Chen , Arnav Jhala

The age of social media is rife with memes. Understanding and detecting harmful memes pose a significant challenge due to their implicit meaning that is not explicitly conveyed through the surface text and image. However, existing harmful…

计算与语言 · 计算机科学 2023-12-12 Hongzhan Lin , Ziyang Luo , Jing Ma , Long Chen