中文
相关论文

相关论文: Analyzing Narrative Processing in Large Language M…

200 篇论文

As interest in economic narratives has grown in recent years, so has the number of pipelines dedicated to extracting such narratives from texts. Pipelines often employ a mix of state-of-the-art natural language processing techniques, such…

Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities of…

计算机视觉与模式识别 · 计算机科学 2024-12-02 Shukang Yin , Chaoyou Fu , Sirui Zhao , Ke Li , Xing Sun , Tong Xu , Enhong Chen

A Large Language Model (LLM) is an artificial intelligence system that has been trained on vast amounts of natural language data, enabling it to generate human-like responses to written or spoken language input. GPT-3.5 is an example of an…

人工智能 · 计算机科学 2023-05-09 Gaurav Suri , Lily R. Slater , Ali Ziaee , Morgan Nguyen

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

人工智能 · 计算机科学 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Pretrained language models (PLMs) form the basis of most state-of-the-art NLP technologies. Nevertheless, they are essentially black boxes: Humans do not have a clear understanding of what knowledge is encoded in different parts of the…

计算与语言 · 计算机科学 2023-11-15 Tanja Baeumel , Soniya Vijayakumar , Josef van Genabith , Guenter Neumann , Simon Ostermann

Large Language Models (LLMs) have revolutionized natural language processing (NLP) by delivering state-of-the-art performance across a variety of tasks. Among these, Transformer-based models like BERT and GPT rely on pooling layers to…

计算与语言 · 计算机科学 2025-02-04 Jinming Xing , Dongwen Luo , Chang Xue , Ruilin Xing

Large Language Models (LLMs) offer numerous applications, the full extent of which is not yet understood. This paper investigates if LLMs can be applied for editing structured and semi-structured documents with minimal effort. Using a…

机器学习 · 计算机科学 2024-09-16 Irene Weber

Recently, Natural Language Processing (NLP) has witnessed an impressive progress in many areas, due to the advent of novel, pretrained contextual representation models. In particular, Devlin et al. (2019) proposed a model, called BERT…

计算与语言 · 计算机科学 2020-03-09 Debora Nozza , Federico Bianchi , Dirk Hovy

Logical reasoning is a fundamental aspect of human intelligence and a key component of tasks like problem-solving and decision-making. Recent advancements have enabled Large Language Models (LLMs) to potentially exhibit reasoning…

计算与语言 · 计算机科学 2023-11-13 Jiazhan Feng , Ruochen Xu , Junheng Hao , Hiteshi Sharma , Yelong Shen , Dongyan Zhao , Weizhu Chen

Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and newly found emergent capability (e.g., reasoning). While LLMs…

计算与语言 · 计算机科学 2024-11-22 Bowen Jin , Gang Liu , Chi Han , Meng Jiang , Heng Ji , Jiawei Han

In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained…

人机交互 · 计算机科学 2024-03-22 Younes Lakhnati , Max Pascher , Jens Gerken

There is enormous enthusiasm and concerns in using large language models (LLMs) in healthcare, yet current assumptions are all based on general-purpose LLMs such as ChatGPT. This study develops a clinical generative LLM, GatorTronGPT, using…

Foundational Language Models (FLMs) have advanced natural language processing (NLP) research. Current researchers are developing larger FLMs (e.g., XLNet, T5) to enable contextualized language representation, classification, and generation.…

计算与语言 · 计算机科学 2023-08-24 Nancy Tyagi , Aidin Shiri , Surjodeep Sarkar , Abhishek Kumar Umrawal , Manas Gaur

Large, pre-trained transformer-based language models such as BERT have drastically changed the Natural Language Processing (NLP) field. We present a survey of recent work that uses these large language models to solve NLP tasks via…

Large Language Models (LLMs) have revolutionized the field of Natural Language Processing thanks to their ability to reuse knowledge acquired on massive text corpora on a wide variety of downstream tasks, with minimal (if any) tuning steps.…

计算与语言 · 计算机科学 2024-07-12 Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti

Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholinguistic models, DLMs use layered sequences of continuous…

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) 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

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

Modern Artificial Intelligence applications show great potential for language-related tasks that rely on next-word prediction. The current generation of Large Language Models (LLMs) have been linked to claims about human-like linguistic…

计算与语言 · 计算机科学 2024-09-05 Evelina Leivada , Gary Marcus , Fritz Günther , Elliot Murphy