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Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of…

定量方法 · 定量生物学 2025-02-04 Jiajia Liu , Mengyuan Yang , Yankai Yu , Haixia Xu , Tiangang Wang , Kang Li , Xiaobo Zhou

Humankind's understanding of the world is fundamentally linked to our perception and cognition, with \emph{human languages} serving as one of the major carriers of \emph{world knowledge}. In this vein, \emph{Large Language Models} (LLMs)…

人工智能 · 计算机科学 2024-06-27 Huajun Chen

Based on official estimates, 50 million people worldwide are affected by dementia, and this number increases by 10 million new patients every year. Without a cure, clinical prognostication and early intervention represent the most effective…

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

Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic community has intensified its investigations into LLMs with…

The NLP community recently saw the release of a new large open-access multilingual language model, BLOOM (BigScience et al., 2022) covering 46 languages. We focus on BLOOM's multilingual ability by evaluating its machine translation…

计算与语言 · 计算机科学 2023-05-10 Rachel Bawden , François Yvon

Large Language Models (LLMs) have demonstrated remarkable performance across various information-seeking and reasoning tasks. These computational systems drive state-of-the-art dialogue systems, such as ChatGPT and Bard. They also carry…

计算与语言 · 计算机科学 2023-10-13 Siyuan Brandon Loh , Aravind Sesagiri Raamkumar

Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations. Inspired by the global paradigm shift in NLP towards Large Language Models (LLMs),…

计算与语言 · 计算机科学 2024-02-27 Yaoyiran Li , Anna Korhonen , Ivan Vulić

The performance of NLP methods for severely under-resourced languages cannot currently hope to match the state of the art in NLP methods for well resourced languages. We explore the extent to which pretrained large language models (LLMs)…

计算与语言 · 计算机科学 2024-02-20 Michela Lorandi , Anya Belz

ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text…

$\textbf{Objectives}$: Large Language Models (LLMs) such as ChatGPT and Med-PaLM have excelled in various medical question-answering tasks. However, these English-centric models encounter challenges in non-English clinical settings,…

计算与语言 · 计算机科学 2024-01-31 Jiageng Wu , Xian Wu , Zhaopeng Qiu , Minghui Li , Yingying Zhang , Yefeng Zheng , Changzheng Yuan , Jie Yang

Large language models (LLMs) have demonstrated remarkable open-domain capabilities. LLMs tailored for a domain are typically trained entirely on domain corpus to excel at handling domain-specific tasks. In this work, we explore an…

计算与语言 · 计算机科学 2026-01-13 Yong Xie , Karan Aggarwal , Aitzaz Ahmad

The advancements in the Large Language Model (LLM) have helped in solving several problems related to language processing. Most of the researches have focused on the English language only, because of its popularity and abundance on the…

计算与语言 · 计算机科学 2024-12-31 Sanjay Chouhan , Shubha Brata Nath , Aparajita Dutta

Recent development of large-scale pre-trained language models (PLM) have significantly improved the capability of models in various NLP tasks, in terms of performance after task-specific fine-tuning and zero-shot / few-shot learning.…

计算与语言 · 计算机科学 2022-04-21 Chenguang Zhu , Michael Zeng

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

计算与语言 · 计算机科学 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

While large language models have facilitated breakthroughs in many applications of artificial intelligence, their inherent largeness makes them computationally expensive and challenging to deploy in resource-constrained settings. In this…

Various deep learning-based approaches utilizing pre-trained language models (PLMs) have been proposed for automated vulnerability detection. With recent advancements in large language models (LLMs), several studies have begun exploring…

软件工程 · 计算机科学 2026-03-11 Honglin Shu , Michael Fu , Junji Yu , Dong Wang , Chakkrit Tantithamthavorn , Junjie Chen , Yasutaka Kamei

This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics. Our examination involves a…

Large language models (LLMs) such as ChatGPT, Gemini, LlaMa, and Claude are trained on massive quantities of text parsed from the internet and have shown a remarkable ability to respond to complex prompts in a manner often indistinguishable…

光学 · 物理学 2025-04-01 Darui Lu , Yang Deng , Jordan M. Malof , Willie J. Padilla

Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks. In this work, our aim is to explore the multilingual capabilities of large language models by using machine translation as a task involving…

Evaluating Large Language Models (LLMs) in open-ended scenarios is challenging because existing benchmarks and metrics can not measure them comprehensively. To address this problem, we propose to fine-tune LLMs as scalable judges (JudgeLM)…

计算与语言 · 计算机科学 2025-03-04 Lianghui Zhu , Xinggang Wang , Xinlong Wang