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Large Language Models are cognitively biased judges. Large Language Models (LLMs) have recently been shown to be effective as automatic evaluators with simple prompting and in-context learning. In this work, we assemble 15 LLMs of four…

计算与语言 · 计算机科学 2024-09-26 Ryan Koo , Minhwa Lee , Vipul Raheja , Jong Inn Park , Zae Myung Kim , Dongyeop Kang

Large Language Models (LLMs) have shown remarkable promise in communicating with humans. Their potential use as artificial partners with humans in sociological experiments involving conversation is an exciting prospect. But how viable is…

人工智能 · 计算机科学 2025-02-04 James Flamino , Mohammed Shahid Modi , Boleslaw K. Szymanski , Brendan Cross , Colton Mikolajczyk

Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue capabilities by leveraging instruction tuning, which refreshes human impressions of dialogue systems. The long-standing goal of dialogue systems is to be…

计算与语言 · 计算机科学 2024-04-01 Jiao Ou , Junda Lu , Che Liu , Yihong Tang , Fuzheng Zhang , Di Zhang , Kun Gai

Large Language Models (LLMs), such as ChatGPT, exhibit advanced capabilities in generating text, images, and videos. However, their effective use remains constrained by challenges in prompt formulation, personalization, and opaque…

人机交互 · 计算机科学 2025-03-04 Si Thu , A. Baki Kocaballi

Language models (LMs) are increasingly used to simulate human-like responses in scenarios where accurately mimicking a population's behavior can guide decision-making, such as in developing educational materials and designing public…

计算与语言 · 计算机科学 2024-07-23 Joy He-Yueya , Wanjing Anya Ma , Kanishk Gandhi , Benjamin W. Domingue , Emma Brunskill , Noah D. Goodman

Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the development of agents that support human-machine dialogue interaction…

计算机视觉与模式识别 · 计算机科学 2023-11-07 Zhenfei Yin , Jiong Wang , Jianjian Cao , Zhelun Shi , Dingning Liu , Mukai Li , Lu Sheng , Lei Bai , Xiaoshui Huang , Zhiyong Wang , Jing Shao , Wanli Ouyang

With large language models (LLMs) becoming increasingly prevalent in daily life, so too has the tendency to attribute to them human-like minds and emotions, or anthropomorphize them. Here, we investigate dimensions people use to…

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 goal of achieving Artificial General Intelligence (AGI) is to imitate humans and surpass them. Models such as OpenAI's o1, o3, and DeepSeek's R1 have demonstrated that large language models (LLMs) with human-like reasoning capabilities…

计算机视觉与模式识别 · 计算机科学 2025-05-27 Yansheng Qiu , Li Xiao , Zhaopan Xu , Pengfei Zhou , Zheng Wang , Kaipeng Zhang

Humans act via a nuanced process that depends both on rational deliberation and also on identity and contextual factors. In this work, we study how large language models (LLMs) can simulate human action in the context of social dilemma…

计算与语言 · 计算机科学 2026-02-03 Suhong Moon , Minwoo Kang , Joseph Suh , Mustafa Safdari , John Canny

We introduce TableLLM, a robust large language model (LLM) with 8 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embedded within documents or spreadsheets, catering to…

Evaluating reasoning ability in Large Language Models (LLMs) is important for advancing artificial intelligence, as it transcends mere linguistic task performance. It involves understanding whether these models truly understand information,…

人工智能 · 计算机科学 2025-10-29 Benjamin Grando Moreira

Understanding whether large language models (LLMs) and the human brain converge on similar computational principles remains a fundamental and important question in cognitive neuroscience and AI. Do the brain-like patterns observed in LLMs…

计算与语言 · 计算机科学 2025-12-03 Yu Lei , Xingyang Ge , Yi Zhang , Yiming Yang , Bolei Ma

Large language models (LLMs) are increasingly used as automated judges to evaluate recommendation systems, search engines, and other subjective tasks, where relying on human evaluators can be costly, time-consuming, and unscalable. LLMs…

计算与语言 · 计算机科学 2025-02-10 Gerrit J. J. van den Burg , Gen Suzuki , Wei Liu , Murat Sensoy

Large Language Models (LLMs) have been shown to be effective models of the human language system, with some models predicting most explainable variance of brain activity in current datasets. Even in untrained models, the representations…

计算与语言 · 计算机科学 2024-06-24 Badr AlKhamissi , Greta Tuckute , Antoine Bosselut , Martin Schrimpf

Can AI systems like large language models (LLMs) replace human participants in behavioral and psychological research? Here I critically evaluate the "replacement" perspective and identify six interpretive fallacies that undermine its…

计算机与社会 · 计算机科学 2025-08-18 Zhicheng Lin

Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and text summarization. We provide a simple new prompting strategy…

计算与语言 · 计算机科学 2022-12-14 Joshua Albrecht , Ellie Kitanidis , Abraham J. Fetterman

Psychological profiling of large language models (LLMs) using psychometric questionnaires designed for humans has become widespread. However, it remains unclear whether the resulting profiles mirror the models' psychological characteristics…

计算与语言 · 计算机科学 2026-04-06 Woojung Song , Dongmin Choi , Yoonah Park , Jongwook Han , Yohan Jo

This study validates Large Language Models (LLMs) as a dynamic alternative to questionnaire-based personality assessment. Using a within-subjects experiment (N=33), we compared Big Five personality scores derived from guided LLM…

计算与语言 · 计算机科学 2026-02-19 Andrius Matšenas , Anet Lello , Tõnis Lees , Hans Peep , Kim Lilii Tamm

Large Language Models are typically trained with next-turn rewards, limiting their ability to optimize for long-term interaction. As a result, they often respond passively to ambiguous or open-ended user requests, failing to help users…

人工智能 · 计算机科学 2025-07-31 Shirley Wu , Michel Galley , Baolin Peng , Hao Cheng , Gavin Li , Yao Dou , Weixin Cai , James Zou , Jure Leskovec , Jianfeng Gao