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Applications built on top of Large Language Models (LLMs) such as GPT-4 represent a revolution in AI due to their human-level capabilities in natural language processing. However, they also pose many significant risks such as the presence…

In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities…

计算与语言 · 计算机科学 2024-03-22 Hanieh Alipour , Nick Pendar , Kohinoor Roy

Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit…

计算与语言 · 计算机科学 2023-10-20 Katikapalli Subramanyam Kalyan

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

计算与语言 · 计算机科学 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations…

Generative pre-trained transformer (GPT) models have revolutionized the field of natural language processing (NLP) with remarkable performance in various tasks and also extend their power to multimodal domains. Despite their success, large…

计算与语言 · 计算机科学 2023-08-29 Kaiyuan Gao , Sunan He , Zhenyu He , Jiacheng Lin , QiZhi Pei , Jie Shao , Wei Zhang

Large Language Models (LLMs) have revo lutionized natural language processing Natural Language Processing (NLP), with Chat Generative Pre-trained Transformer (ChatGPT) standing out as a notable exampledue to its advanced capabilities and…

计算与语言 · 计算机科学 2025-03-25 Azim Akhtarshenas , Afshin Dini , Navid Ayoobi

Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on…

分布式、并行与集群计算 · 计算机科学 2024-07-09 Mario Sänger , Ninon De Mecquenem , Katarzyna Ewa Lewińska , Vasilis Bountris , Fabian Lehmann , Ulf Leser , Thomas Kosch

Generative Large Language Models (gLLMs), such as ChatGPT, are increasingly being used in communication research for content analysis. Studies show that gLLMs can outperform both crowd workers and trained coders, such as research…

人工智能 · 计算机科学 2025-10-29 Daria Kravets-Meinke , Hannah Schmid-Petri , Sonja Niemann , Ute Schmid

Large language models (LLMs) have recently achieved human-level performance on a range of professional and academic benchmarks. The accessibility of these models has lagged behind their performance. State-of-the-art LLMs require costly…

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Large Language Models (LLMs) represent a revolution in AI. However, they also pose many significant risks, such as the presence of biased, private, copyrighted or harmful text. For this reason we need open, transparent and safe solutions.…

计算与语言 · 计算机科学 2023-10-24 Arno Candel , Jon McKinney , Philipp Singer , Pascal Pfeiffer , Maximilian Jeblick , Chun Ming Lee , Marcos V. Conde

In 2022, with the release of ChatGPT, large-scale language models gained widespread attention. ChatGPT not only surpassed previous models in terms of parameters and the scale of its pretraining corpus but also achieved revolutionary…

人工智能 · 计算机科学 2024-11-13 Yiming Ju , Huanhuan Ma

The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative…

In recent years, groundbreaking advancements in natural language processing have culminated in the emergence of powerful large language models (LLMs), which have showcased remarkable capabilities across a vast array of domains, including…

计算与语言 · 计算机科学 2023-12-11 Microsoft Research AI4Science , Microsoft Azure Quantum

This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (NLP) tasks. We provide discussions and insights into the…

计算与语言 · 计算机科学 2023-04-28 Jingfeng Yang , Hongye Jin , Ruixiang Tang , Xiaotian Han , Qizhang Feng , Haoming Jiang , Bing Yin , Xia Hu

Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntactically correct content. Despite challenges like biases and…

计算与语言 · 计算机科学 2025-08-04 Alper Yaman , Jannik Schwab , Christof Nitsche , Abhirup Sinha , Marco Huber

This paper identifies and analyzes applications in which Large Language Models (LLMs) can make Internet of Things (IoT) networks more intelligent and responsive through three case studies from critical topics: DDoS attack detection,…

人工智能 · 计算机科学 2024-10-28 Mingyu Zong , Arvin Hekmati , Michael Guastalla , Yiyi Li , Bhaskar Krishnamachari

Large Language Models (LLMs) are transforming AI across industries, but their development and deployment remain complex. This survey reviews 16 key challenges in building and using LLMs and examines how these challenges are addressed by two…

计算与语言 · 计算机科学 2025-09-01 Shubham Sharma , Sneha Tuli , Narendra Badam

Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans. However, LLMs still struggle to generate natural and colloquial responses in…

计算与语言 · 计算机科学 2024-10-16 Renliang Sun , Mengyuan Liu , Shiping Yang , Rui Wang , Junqing He , Jiaxing Zhang
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