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

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Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification.…

计算与语言 · 计算机科学 2024-08-12 Md Nazmus Sakib , Md Athikul Islam , Royal Pathak , Md Mashrur Arifin

Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in…

计算与语言 · 计算机科学 2024-06-24 Yue Huang , Chenrui Fan , Yuan Li , Siyuan Wu , Tianyi Zhou , Xiangliang Zhang , Lichao Sun

Do large language models (LLMs) know the law? These models are increasingly being used to augment legal practice, education, and research, yet their revolutionary potential is threatened by the presence of hallucinations -- textual output…

计算与语言 · 计算机科学 2024-08-09 Matthew Dahl , Varun Magesh , Mirac Suzgun , Daniel E. Ho

With the release of ChatGPT and other large language models (LLMs) the discussion about the intelligence, possibilities, and risks, of current and future models have seen large attention. This discussion included much debated scenarios…

人工智能 · 计算机科学 2024-07-31 Nils Körber , Silvan Wehrli , Christopher Irrgang

Large language models (LLMs) have demonstrated impressive capabilities across a variety of tasks, but their increasing autonomy in real-world applications raises concerns about their trustworthiness. While hallucinations-unintentional…

机器学习 · 计算机科学 2025-09-04 Haoran Huan , Mihir Prabhudesai , Mengning Wu , Shantanu Jaiswal , Deepak Pathak

The recent performance leap of Large Language Models (LLMs) opens up new opportunities across numerous industrial applications and domains. However, erroneous generations, such as false predictions, misinformation, and hallucination made by…

软件工程 · 计算机科学 2025-01-07 Yuheng Huang , Jiayang Song , Zhijie Wang , Shengming Zhao , Huaming Chen , Felix Juefei-Xu , Lei Ma

Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPMs) for diagnostic and prognostic tasks, with a focus on…

计算机与社会 · 计算机科学 2025-11-07 Yusuf Yildiz , Goran Nenadic , Meghna Jani , David A. Jenkins

Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the digital landscape, two growing concerns emerge in…

计算与语言 · 计算机科学 2024-04-24 Raphael Poulain , Hamed Fayyaz , Rahmatollah Beheshti

As artificial intelligence (AI) systems, particularly large language models (LLMs), become increasingly integrated into decision-making processes, the ability to trust their outputs is crucial. To earn human trust, LLMs must be well…

Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in critical scenarios. This paper introduces a rigorously…

计算与语言 · 计算机科学 2023-11-21 Saizhuo Wang , Zhihan Liu , Zhaoran Wang , Jian Guo

Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective on using LLMs in mental health applications. It discusses…

计算与语言 · 计算机科学 2023-12-19 Shaoxiong Ji , Tianlin Zhang , Kailai Yang , Sophia Ananiadou , Erik Cambria

The advent of large language models (LLMs) has enabled significant performance gains in the field of natural language processing. However, recent studies have found that LLMs often resort to shortcuts when performing tasks, creating an…

计算与语言 · 计算机科学 2024-12-18 Geetanjali Bihani , Julia Taylor Rayz

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks in various domains. Despite their impressive performance, they can be unreliable due to factual errors in their generations. Assessing their…

计算与语言 · 计算机科学 2024-03-26 Jiahui Geng , Fengyu Cai , Yuxia Wang , Heinz Koeppl , Preslav Nakov , Iryna Gurevych

Advancements in Large Language Models (LLMs) have increased the performance of different natural language understanding as well as generation tasks. Although LLMs have breached the state-of-the-art performance in various tasks, they often…

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

计算与语言 · 计算机科学 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

This report analyzes key trends, challenges, risks, and opportunities associated with the development of Large Language Models (LLMs) globally. It examines national experiences in developing LLMs and assesses the feasibility of investment…

Large Language Models (LLMs) have emerged with many intellectual capacities. While numerous benchmarks assess their intelligence, limited attention has been given to their ability to explore--an essential capacity for discovering new…

人工智能 · 计算机科学 2025-05-13 Lan Pan , Hanbo Xie , Robert C. Wilson

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

Large language models (LLMs) are increasingly prevalent in security research. Their unique characteristics, however, introduce challenges that undermine established paradigms of reproducibility, rigor, and evaluation. Prior work has…

Large Language Models (LLMs) are transforming writing, reading, teaching, and knowledge retrieval in many academic fields. However, concerns regarding their misuse and erroneous outputs have led to varying degrees of trust in LLMs within…

计算机与社会 · 计算机科学 2025-02-10 Minseok Jung , Aurora Zhang , May Fung , Junho Lee , Paul Pu Liang