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Language models have emerged as a critical area of focus in artificial intelligence, particularly with the introduction of groundbreaking innovations like ChatGPT. Large-scale Transformer networks have quickly become the leading approach…

人工智能 · 计算机科学 2024-12-12 Wei Wang , Qing Li

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

Transfer learning in Reinforcement Learning (RL) enables agents to leverage knowledge from source tasks to accelerate learning in target tasks. While prior work, such as the Attend, Adapt, and Transfer (A2T) framework, addresses negative…

机器学习 · 计算机科学 2025-07-08 Abhishek Verma , Nallarasan V , Balaraman Ravindran

The usefulness of Large Language Models (LLM) is being continuously tested in various fields. However, their intrinsic linguistic characteristic is still one of the limiting factors when applying these models to exact sciences. In this…

人工智能 · 计算机科学 2024-09-24 Jonathan Paul Driemeyer Brown , Tiago Oliveira Weber

Large Language Models (LLMs) have demonstrated remarkable zero-shot generalization across various language-related tasks, including search engines. However, existing work utilizes the generative ability of LLMs for Information Retrieval…

计算与语言 · 计算机科学 2024-12-31 Weiwei Sun , Lingyong Yan , Xinyu Ma , Shuaiqiang Wang , Pengjie Ren , Zhumin Chen , Dawei Yin , Zhaochun Ren

Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

计算与语言 · 计算机科学 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

Large language models (LLMs) like GPT-4 and LLaMA-3 utilize the powerful in-context learning (ICL) capability of Transformer architecture to learn on the fly from limited examples. While ICL underpins many LLM applications, its full…

机器学习 · 计算机科学 2025-03-21 Xingxuan Zhang , Haoran Wang , Jiansheng Li , Yuan Xue , Shikai Guan , Renzhe Xu , Hao Zou , Han Yu , Peng Cui

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…

Interest in Large Language Models (LLMs) has increased drastically since the emergence of ChatGPT and the outstanding positive societal response to the ease with which it performs tasks in Natural Language Processing (NLP). The triumph of…

计算与语言 · 计算机科学 2023-04-06 Oluwatosin Ogundare , Gustavo Quiros Araya

Deep learning (DL) models based on the transformer architecture have revolutionized many DL applications such as large language models (LLMs), vision transformers, audio generation, and time series prediction. Much of this progress has been…

分布式、并行与集群计算 · 计算机科学 2024-08-20 Quentin Anthony , Benjamin Michalowicz , Jacob Hatef , Lang Xu , Mustafa Abduljabbar , Aamir Shafi , Hari Subramoni , Dhabaleswar Panda

Large Language Models (LLMs) such as ChatGPT have transformed how we interact with and understand the capabilities of Artificial Intelligence (AI). However, the intersection of LLMs with the burgeoning field of Quantum Machine Learning…

量子物理 · 物理学 2024-03-15 Yidong Liao , Chris Ferrie

Recent advancements in Large Language Models (LLMs), particularly those built on Transformer architectures, have significantly broadened the scope of natural language processing (NLP) applications, transcending their initial use in chatbot…

计算与语言 · 计算机科学 2024-05-29 Chen Wang , Jin Zhao , Jiaqi Gong

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities…

计算机与社会 · 计算机科学 2024-01-02 Kevin Wang , Jason Ramos , Ramon Lawrence

Owing to their ability to both effectively integrate information over long time horizons and scale to massive amounts of data, self-attention architectures have recently shown breakthrough success in natural language processing (NLP),…

The introduction of transformer architecture was a turning point in Natural Language Processing (NLP). Models based on the transformer architecture such as Bidirectional Encoder Representations from Transformers (BERT) and Generative…

Transformer architectures contribute to managing long-term dependencies for Natural Language Processing, representing one of the most recent changes in the field. These architectures are the basis of the innovative, cutting-edge Large…

计算与语言 · 计算机科学 2024-09-06 Silvia García-Méndez , Francisco de Arriba-Pérez , María del Carmen Somoza-López

As Large-Scale Language Models (LLMs) continue to evolve, they demonstrate significant enhancements in performance and an expansion of functionalities, impacting various domains, including education. In this study, we conducted interviews…

人机交互 · 计算机科学 2024-07-18 He Zhang , Jingyi Xie , Chuhao Wu , Jie Cai , ChanMin Kim , John M. Carroll

With the continuous development and change exhibited by large language model (LLM) technology, represented by generative pretrained transformers (GPTs), many classic scenarios in various fields have re-emerged with new opportunities. This…

信息检索 · 计算机科学 2024-10-22 Aakas Zhiyuli , Yanfang Chen , Xuan Zhang , Xun Liang

The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There's an increasing focus on cost-efficient training and deployment within this context.…

Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs' MT capabilities. However, there exist a wide variety of languages for which…

计算与语言 · 计算机科学 2023-09-15 Nathaniel R. Robinson , Perez Ogayo , David R. Mortensen , Graham Neubig
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