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相关论文: Training Data for Large Language Model

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The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of large language models has been dramatically improved,…

Large language models (LLMs) such as ChatGPT have gained considerable interest across diverse research communities. Their notable ability for text completion and generation has inaugurated a novel paradigm for language-interfaced problem…

Large Language Models (LLMs) have seen great advance in both academia and industry, and their popularity results in numerous open-source frameworks and techniques in accelerating LLM pre-training, fine-tuning, and inference. Training and…

ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction about the development of large language models (LLMs). Next,…

计算与语言 · 计算机科学 2023-09-07 Ou Zheng , Mohamed Abdel-Aty , Dongdong Wang , Zijin Wang , Shengxuan Ding

The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable. Nevertheless, these models typically perform better in English and have not been…

计算与语言 · 计算机科学 2023-04-18 Honglin Xiong , Sheng Wang , Yitao Zhu , Zihao Zhao , Yuxiao Liu , Linlin Huang , Qian Wang , Dinggang Shen

In the era of sustainable smart agriculture, a massive amount of agricultural news text is being posted on the Internet, in which massive agricultural knowledge has been accumulated. In this context, it is urgent to explore effective text…

计算与语言 · 计算机科学 2023-05-25 Biao Zhao , Weiqiang Jin , Javier Del Ser , Guang Yang

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificial general intelligence (AGI). Recently, the integration of…

机器学习 · 计算机科学 2024-12-30 Yang Gu , Hengyu You , Jian Cao , Muran Yu , Haoran Fan , Shiyou Qian

The past few decades have witnessed an upsurge in data, forming the foundation for data-hungry, learning-based AI technology. Conversational agents, often referred to as AI chatbots, rely heavily on such data to train large language models…

计算与语言 · 计算机科学 2024-11-19 Sumit Kumar Dam , Choong Seon Hong , Yu Qiao , Chaoning Zhang

Since the release of GPT2-1.5B in 2019, the large language models (LLMs) have evolved from specialized deep models to versatile foundation models. While demonstrating remarkable zero-shot ability, the LLMs still require fine-tuning on local…

人工智能 · 计算机科学 2025-08-07 Yanjie Dong , Haijun Zhang , Chengming Li , Song Guo , Victor C. M. Leung , Xiping Hu

This position paper proposes a data-centric viewpoint of AI research, focusing on large language models (LLMs). We start by making the key observation that data is instrumental in the developmental (e.g., pretraining and fine-tuning) and…

Large language models (LLMs) like ChatGPT have exhibited remarkable abilities on a wide range of natural language processing~(NLP) tasks, including various machine translation abilities accomplished during chat. However, these models are…

计算与语言 · 计算机科学 2023-11-03 Wenxiang Jiao , Jen-tse Huang , Wenxuan Wang , Zhiwei He , Tian Liang , Xing Wang , Shuming Shi , Zhaopeng Tu

As a way of addressing increasingly sophisticated problems, software professionals face the constant challenge of seeking improvement. However, for these individuals to enhance their skills, their process of studying and training must…

Human-produced emissions are growing at an alarming rate, causing already observable changes in the climate and environment in general. Each year global carbon dioxide emissions hit a new record, and it is reported that 0.5% of total US…

计算机与社会 · 计算机科学 2024-08-06 Aida Usmanova , Junbo Huang , Debayan Banerjee , Ricardo Usbeck

How do large language models (LLMs) develop and evolve over the course of training? How do these patterns change as models scale? To answer these questions, we introduce \textit{Pythia}, a suite of 16 LLMs all trained on public data seen in…

Multimodal large language models (MLLMs) enhance the capabilities of standard large language models by integrating and processing data from multiple modalities, including text, vision, audio, video, and 3D environments. Data plays a pivotal…

Language model (LLM) post-training, from DPO to distillation, can refine behaviors and unlock new skills, but the open science supporting these post-training techniques is still in its infancy. One limiting factor has been the difficulty of…

机器学习 · 计算机科学 2025-05-26 Benjamin Feuer , Chinmay Hegde

In the swiftly expanding domain of Natural Language Processing (NLP), the potential of GPT-based models for the financial sector is increasingly evident. However, the integration of these models with financial datasets presents challenges,…

计算与语言 · 计算机科学 2023-11-14 Neng Wang , Hongyang Yang , Christina Dan Wang

Gestures perform a variety of communicative functions that powerfully influence human face-to-face interaction. How this communicative function is achieved varies greatly between individuals and depends on the role of the speaker and the…

人机交互 · 计算机科学 2023-10-24 Laura B. Hensel , Nutchanon Yongsatianchot , Parisa Torshizi , Elena Minucci , Stacy Marsella

Large Language Models (LLMs), particularly those similar to ChatGPT, have significantly influenced the field of Natural Language Processing (NLP). While these models excel in general language tasks, their performance in domain-specific…

计算与语言 · 计算机科学 2024-01-02 Omid Rohanian , Mohammadmahdi Nouriborji , David A. Clifton

The rapid advancement of large language models (LLMs) has significantly advanced the capabilities of artificial intelligence across various domains. However, their massive scale and high computational costs render them unsuitable for direct…

计算机视觉与模式识别 · 计算机科学 2025-10-01 Miao Rang , Zhenni Bi , Hang Zhou , Hanting Chen , An Xiao , Tianyu Guo , Kai Han , Xinghao Chen , Yunhe Wang