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相关论文: Eight Things to Know about Large Language Models

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Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of…

密码学与安全 · 计算机科学 2024-02-28 Gabriel de Jesus Coelho da Silva , Carlos Becker Westphall

Large language models (LLMs) have shown impressive capabilities across a wide range of language tasks. However, their reasoning process is primarily guided by statistical patterns in training data, which limits their ability to handle novel…

人工智能 · 计算机科学 2025-08-21 Hong Su

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase…

人机交互 · 计算机科学 2025-03-24 Michelle Brachman , Amina El-Ashry , Casey Dugan , Werner Geyer

Large Language Models (LLMs) are frequently utilized as sources of knowledge for question-answering. While it is known that LLMs may lack access to real-time data or newer data produced after the model's cutoff date, it is less clear how…

计算与语言 · 计算机科学 2025-07-30 Agam Shah , Liqin Ye , Sebastian Jaskowski , Wei Xu , Sudheer Chava

Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks. From natural language processing and sentiment analysis to…

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future…

机器学习 · 计算机科学 2024-02-19 Jing Su , Chufeng Jiang , Xin Jin , Yuxin Qiao , Tingsong Xiao , Hongda Ma , Rong Wei , Zhi Jing , Jiajun Xu , Junhong Lin

Large language models (LLMs) are demonstrably capable of cross-lingual transfer, but can produce inconsistent output when prompted with the same queries written in different languages. To understand how language models are able to…

计算与语言 · 计算机科学 2025-09-29 Zheng Wei Lim , Alham Fikri Aji , Trevor Cohn

In order for AI systems to communicate effectively with people, they must understand how we make decisions. However, people's decisions are not always rational, so the implicit internal models of human decision-making in Large Language…

计算与语言 · 计算机科学 2025-03-11 Ryan Liu , Jiayi Geng , Joshua C. Peterson , Ilia Sucholutsky , Thomas L. Griffiths

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

Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work has been done on investigating the pedagogical ability of…

计算与语言 · 计算机科学 2023-10-23 An-Zi Yen , Wei-Ling Hsu

Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge engineering and artificial intelligence. Recently, Large Language Models (LLMs) have emerged as a noteworthy innovation in natural language…

计算与语言 · 计算机科学 2024-09-17 Fangzhi Xu , Qika Lin , Jiawei Han , Tianzhe Zhao , Jun Liu , Erik Cambria

Recent advances in Large Language Models (LLMs) highlight the need to align their behaviors with human values. A critical, yet understudied, issue is the potential divergence between an LLM's stated preferences (its reported alignment with…

人工智能 · 计算机科学 2025-06-03 Zhuojun Gu , Quan Wang , Shuchu Han

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

Large Language Models (LLMs) have demonstrated exceptional capabilities in solving various tasks, progressively evolving into general-purpose assistants. The increasing integration of LLMs into society has sparked interest in whether they…

计算与语言 · 计算机科学 2025-10-20 Yuan Li , Yue Huang , Hongyi Wang , Ying Cheng , Xiangliang Zhang , James Zou , Lichao Sun

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code…

材料科学 · 物理学 2024-10-22 Ge Lei , Ronan Docherty , Samuel J. Cooper

A Language Model is a term that encompasses various types of models designed to understand and generate human communication. Large Language Models (LLMs) have gained significant attention due to their ability to process text with human-like…

Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing management. In this paper, we explore the transformative potential of LLMs along with the…

计算与语言 · 计算机科学 2025-01-22 Raha Aghaei , Ali A. Kiaei , Mahnaz Boush , Javad Vahidi , Mohammad Zavvar , Zeynab Barzegar , Mahan Rofoosheh

Large Language Models (LLMs) excel in handling general knowledge tasks, yet they struggle with user-specific personalization, such as understanding individual emotions, writing styles, and preferences. Personalized Large Language Models…

人工智能 · 计算机科学 2025-09-23 Jiahong Liu , Zexuan Qiu , Zhongyang Li , Quanyu Dai , Wenhao Yu , Jieming Zhu , Minda Hu , Menglin Yang , Tat-Seng Chua , Irwin King

Large language models (LLMs) have demonstrated unprecedented emergent capabilities, including content generation, translation, and simulation of human behavior. Field experiments, on the other hand, are widely employed in social studies to…

计算机与社会 · 计算机科学 2025-05-22 Yaoyu Chen , Yuheng Hu , Yingda Lu

Large Language Models (LLMs) have emerged as dominant foundational models in modern NLP. However, the understanding of their prediction processes and internal mechanisms, such as feed-forward networks (FFN) and multi-head self-attention…

计算与语言 · 计算机科学 2024-04-16 Xintong Wang , Xiaoyu Li , Xingshan Li , Chris Biemann