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Large Language Models (LLMs) can be deployed in situations where they process positive/negative interactions with other agents. We study how this is done under the sociological framework of social balance, which explains the emergence of…

计算与语言 · 计算机科学 2026-01-07 Pedro Cisneros-Velarde

Evaluating the creative capabilities of large language models (LLMs) in complex tasks often requires human assessments that are difficult to scale. We introduce a novel, scalable methodology for evaluating LLM story generation by analyzing…

计算与语言 · 计算机科学 2025-10-23 Hiroshi Nonaka , K. E. Perry

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

Large Language Models (LLMs) are extensively used today across various sectors, including academia, research, business, and finance, for tasks such as text generation, summarization, and translation. Despite their widespread adoption, these…

计算与语言 · 计算机科学 2024-04-26 Yash Saxena , Sarthak Chopra , Arunendra Mani Tripathi

Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues. In this paper, we develop a quantitative framework to evaluate whose opinions model-generated responses are more similar to. We first…

Large language models (LLMs) have transformed natural language processing, achieving remarkable performance across diverse tasks. However, their impressive fluency often comes at the cost of producing false or fabricated information, a…

计算与语言 · 计算机科学 2026-03-20 Aisha Alansari , Hamzah Luqman

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) possess general world knowledge but often struggle to generate precise predictions in structured, domain-specific contexts such as simulations. These limitations arise from their inability to ground their broad,…

人工智能 · 计算机科学 2026-01-30 Guillaume Levy , Cedric Colas , Pierre-Yves Oudeyer , Thomas Carta , Clement Romac

The ability of Large Language Models (LLMs) to perform reasoning tasks such as deduction has been widely investigated in recent years. Yet, their capacity to generate proofs-faithful, human-readable explanations of why conclusions…

人工智能 · 计算机科学 2026-01-21 Hui Yang , Jiaoyan Chen , Uli Sattler

Large language models (LLMs) have recently emerged as a powerful tool for a wide range of language generation tasks. Nevertheless, this progress has been slower in Arabic. In this work, we focus on the task of generating stories from LLMs.…

计算与语言 · 计算机科学 2024-07-11 Ahmed Oumar El-Shangiti , Fakhraddin Alwajih , Muhammad Abdul-Mageed

Large Language Models (LLMs) are increasingly used to simulate public opinion and other social phenomena. Most current studies constrain these simulations to multiple-choice or short-answer formats for ease of scoring and comparison, but…

计算与语言 · 计算机科学 2026-03-17 Bolei Ma , Yong Cao , Indira Sen , Anna-Carolina Haensch , Frauke Kreuter , Barbara Plank , Daniel Hershcovich

Large language models (LLMs) have made remarkable progress in a wide range of natural language understanding and generation tasks. However, their ability to generate counterfactuals has not been examined systematically. To bridge this gap,…

计算与语言 · 计算机科学 2024-02-26 Yongqi Li , Mayi Xu , Xin Miao , Shen Zhou , Tieyun Qian

The emergence of Large Language Models (LLMs) with increasingly sophisticated natural language understanding and generative capabilities has sparked interest in the Agent-based Modelling (ABM) community. With their ability to summarize,…

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

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

计算与语言 · 计算机科学 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can…

计算与语言 · 计算机科学 2023-05-26 Ronen Eldan , Yuanzhi Li

The current fascination with large language models, or LLMs, derives from the fact that many users lack the expertise to evaluate the quality of the generated text. LLMs may therefore appear more capable than they actually are. The…

计算与语言 · 计算机科学 2024-03-15 Eliza Mik

In recent years, Large Language Models (LLMs) have gained immense attention due to their notable emergent capabilities, surpassing those seen in earlier language models. A particularly intriguing application of LLMs is their role as…

计算与语言 · 计算机科学 2023-11-02 Xue-Yong Fu , Md Tahmid Rahman Laskar , Cheng Chen , Shashi Bhushan TN

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

The use of creative writing as training data for large language models (LLMs) is highly contentious and many writers have expressed outrage at the use of their work without consent or compensation. In this paper, we seek to understand how…

人机交互 · 计算机科学 2025-03-07 Katy Ilonka Gero , Meera Desai , Carly Schnitzler , Nayun Eom , Jack Cushman , Elena L. Glassman