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相关论文: Do LLMs Understand Social Knowledge? Evaluating th…

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Large language models (LLMs) show strong potential for simulating human social behaviors and interactions, yet lack large-scale, systematically constructed benchmarks for evaluating their alignment with real-world social attitudes. To…

社会与信息网络 · 计算机科学 2025-10-14 Jia Wang , Ziyu Zhao , Tingjuntao Ni , Zhongyu Wei

Language models (LMs) trained on large amounts of data have shown impressive performance on many NLP tasks under the zero-shot and few-shot setup. Here we aim to better understand the extent to which such models learn commonsense knowledge…

Large Language Models (LLMs) are capable of successfully performing many language processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify and explain social phenomena like persuasiveness and…

计算与语言 · 计算机科学 2024-02-27 Caleb Ziems , William Held , Omar Shaikh , Jiaao Chen , Zhehao Zhang , Diyi Yang

We present a new challenge to examine whether large language models understand social norms. In contrast to existing datasets, our dataset requires a fundamental understanding of social norms to solve. Our dataset features the largest set…

计算与语言 · 计算机科学 2024-05-24 Ye Yuan , Kexin Tang , Jianhao Shen , Ming Zhang , Chenguang Wang

Humans adjust their linguistic style to the audience they are addressing. However, the extent to which LLMs adapt to different social contexts is largely unknown. As these models increasingly mediate human-to-human communication, their…

计算与语言 · 计算机科学 2026-02-13 Elisa Bassignana , Mike Zhang , Dirk Hovy , Amanda Cercas Curry

Large language models (LLMs) are increasingly applied to socially grounded tasks, such as online community moderation, media content analysis, and social reasoning games. Success in these contexts depends on a model's social reasoning…

As large language models (LLMs) develop anthropomorphic abilities, they are increasingly being deployed as autonomous agents to interact with humans. However, evaluating their performance in realistic and complex social interactions remains…

计算与语言 · 计算机科学 2025-10-28 Shuai Huang , Wenxuan Zhao , Jun Gao

The rise of large language models (LLMs) has significantly impacted various domains, including natural language processing (NLP) and image generation, by making complex computational tasks more accessible. While LLMs demonstrate impressive…

数据库 · 计算机科学 2024-10-15 Ananya Rahaman , Anny Zheng , Mostafa Milani , Fei Chiang , Rachel Pottinger

Large Language Models are expressive tools that enable complex tasks of text understanding within Computational Social Science. Their versatility, while beneficial, poses a barrier for establishing standardized best practices within the…

计算机与社会 · 计算机科学 2024-08-05 Anders Giovanni Møller , Luca Maria Aiello

Sentiment analysis can aid in understanding people's opinions and emotions on social issues. In multilingual communities sentiment analysis systems can be used to quickly identify social challenges in social media posts, enabling government…

计算与语言 · 计算机科学 2025-11-24 Koena Ronny Mabokela , Tim Schlippe , Matthias Wölfel

Large Language Models (LLMs) have remarkable capabilities across NLP tasks. However, their performance in multilingual contexts, especially within the mental health domain, has not been thoroughly explored. In this paper, we evaluate…

计算与语言 · 计算机科学 2026-02-03 Nishat Raihan , Sadiya Sayara Chowdhury Puspo , Ana-Maria Bucur , Stevie Chancellor , Marcos Zampieri

The academic intelligence of large language models (LLMs) has made remarkable progress in recent times, but their social intelligence performance remains unclear. Inspired by established human social intelligence frameworks, particularly…

计算与语言 · 计算机科学 2024-03-12 Ruoxi Xu , Hongyu Lin , Xianpei Han , Le Sun , Yingfei Sun

Large language models (LLMs) have advanced the development of various AI conversational agents, including role-playing conversational agents that mimic diverse characters and human behaviors. While prior research has predominantly focused…

计算与语言 · 计算机科学 2024-08-06 Hongzhan Chen , Hehong Chen , Ming Yan , Wenshen Xu , Xing Gao , Weizhou Shen , Xiaojun Quan , Chenliang Li , Ji Zhang , Fei Huang , Jingren Zhou

Large language models (LLMs) are increasingly being used in a zero-shot fashion to assess mental health conditions, yet we have limited knowledge on what factors affect their accuracy. In this study, we utilize a clinical dataset of natural…

Large Language Models (LLMs) have emerged as highly capable systems and are increasingly being integrated into various uses. However, the rapid pace of their deployment has outpaced a comprehensive understanding of their internal mechanisms…

计算与语言 · 计算机科学 2025-10-27 Gabriele Prato , Jerry Huang , Prasanna Parthasarathi , Shagun Sodhani , Sarath Chandar

Social media discourse involves people from different backgrounds, beliefs, and motives. Thus, often such discourse can devolve into toxic interactions. Generative Models, such as Llama and ChatGPT, have recently exploded in popularity due…

机器学习 · 计算机科学 2024-11-21 Anique Tahir , Lu Cheng , Manuel Sandoval , Yasin N. Silva , Deborah L. Hall , Huan Liu

Understanding context is key to understanding human language, an ability which Large Language Models (LLMs) have been increasingly seen to demonstrate to an impressive extent. However, though the evaluation of LLMs encompasses various…

Large language models (LLMs) like ChatGPT have shown significant advancements across diverse natural language understanding (NLU) tasks, including intelligent dialogue and autonomous agents. Yet, lacking widely acknowledged testing…

计算与语言 · 计算机科学 2024-05-10 Jinyang Wu , Feihu Che , Xinxin Zheng , Shuai Zhang , Ruihan Jin , Shuai Nie , Pengpeng Shao , Jianhua Tao

People have long hoped for a conversational system that can assist in real-life situations, and recent progress on large language models (LLMs) is bringing this idea closer to reality. While LLMs are often impressive in performance, their…

计算与语言 · 计算机科学 2025-02-06 Linkai Peng , Baorian Nuchged , Yingming Gao

Large language models (LLMs) have a wealth of knowledge that allows them to excel in various Natural Language Processing (NLP) tasks. Current research focuses on enhancing their performance within their existing knowledge. Despite their…

计算与语言 · 计算机科学 2023-05-31 Zhangyue Yin , Qiushi Sun , Qipeng Guo , Jiawen Wu , Xipeng Qiu , Xuanjing Huang
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