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ChatGPT and other general large language models (LLMs) have achieved remarkable success, but they have also raised concerns about the misuse of AI-generated texts. Existing AI-generated text detection models, such as based on BERT and…

计算与语言 · 计算机科学 2024-02-05 Rongsheng Wang , Haoming Chen , Ruizhe Zhou , Han Ma , Yaofei Duan , Yanlan Kang , Songhua Yang , Baoyu Fan , Tao Tan

The recent success of Large Language Models (LLMs) has garnered significant attention in both academia and industry. Prior research on LLMs has primarily focused on enhancing or leveraging their generalization capabilities in zero- and…

计算与语言 · 计算机科学 2024-04-01 Shulin Liu , Chengcheng Xu , Hao Liu , Tinghao Yu , Tao Yang

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

Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further…

计算与语言 · 计算机科学 2023-08-01 Yuqing Wang , Yun Zhao , Linda Petzold

Large Language Models (LLMs) have demonstrated surprising performance across various natural language processing tasks. Recently, medical LLMs enhanced with domain-specific knowledge have exhibited excellent capabilities in medical…

计算与语言 · 计算机科学 2024-09-24 Jinqiang Wang , Huansheng Ning , Yi Peng , Qikai Wei , Daniel Tesfai , Wenwei Mao , Tao Zhu , Runhe Huang

Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level machine translation (MT) as a testbed, this paper provides…

计算与语言 · 计算机科学 2023-10-25 Longyue Wang , Chenyang Lyu , Tianbo Ji , Zhirui Zhang , Dian Yu , Shuming Shi , Zhaopeng Tu

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

While the capabilities of Large Language Models (LLMs) have been studied in both Simplified and Traditional Chinese, it is yet unclear whether LLMs exhibit differential performance when prompted in these two variants of written Chinese.…

计算与语言 · 计算机科学 2025-05-29 Hanjia Lyu , Jiebo Luo , Jian Kang , Allison Koenecke

Pretrained Large Language Models (LLMs) have achieved remarkable success across diverse domains, with education and research emerging as particularly impactful areas. Among current state-of-the-art LLMs, ChatGPT and DeepSeek exhibit strong…

人工智能 · 计算机科学 2025-12-10 Md Mostafizer Rahman , Ariful Islam Shiplu , Md Faizul Ibne Amin , Yutaka Watanobe , Lu Peng

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…

Large Language Models (LLMs) have shown promising results on machine translation for high resource language pairs and domains. However, in specialised domains (e.g. medical) LLMs have shown lower performance compared to standard neural…

计算与语言 · 计算机科学 2025-07-31 Miguel Rios

Scientific literature is growing exponentially, creating a critical bottleneck for researchers to efficiently synthesize knowledge. While general-purpose Large Language Models (LLMs) show potential in text processing, they often fail to…

计算与语言 · 计算机科学 2025-09-11 Fengyu She , Nan Wang , Hongfei Wu , Ziyi Wan , Jingmian Wang , Chang Wang

Large language models exhibit promising general capabilities but often lack specialized knowledge for domain-specific tasks. Developing domain experts from a base model enables a range of applications without prohibitive training costs.…

计算与语言 · 计算机科学 2023-11-02 Zhen Guo , Yining Hua

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

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

计算与语言 · 计算机科学 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

As the prevalence of mental health challenges, social media has emerged as a key platform for individuals to express their emotions.Deep learning tends to be a promising solution for analyzing mental health on social media. However, black…

计算与语言 · 计算机科学 2024-10-15 Wei Zhai , Nan Bai , Qing Zhao , Jianqiang Li , Fan Wang , Hongzhi Qi , Meng Jiang , Xiaoqin Wang , Bing Xiang Yang , Guanghui Fu

Large language models (LLMs) have significantly advanced various natural language processing (NLP) tasks. Recent research indicates that moderately-sized LLMs often outperform larger ones after task-specific fine-tuning. This study focuses…

计算与语言 · 计算机科学 2024-10-14 Minghao Wu , Thuy-Trang Vu , Lizhen Qu , George Foster , Gholamreza Haffari

Large language models (LLMs) have obtained promising results in mathematical reasoning, which is a foundational skill for human intelligence. Most previous studies focus on improving and measuring the performance of LLMs based on textual…

计算与语言 · 计算机科学 2024-11-04 Wentao Liu , Qianjun Pan , Yi Zhang , Zhuo Liu , Ji Wu , Jie Zhou , Aimin Zhou , Qin Chen , Bo Jiang , Liang He

Standard multi-task benchmarks are essential for developing pretraining models that can generalize to various downstream tasks. Existing benchmarks for natural language processing (NLP) usually focus only on understanding or generating…

计算与语言 · 计算机科学 2022-01-19 Jian Guan , Zhuoer Feng , Yamei Chen , Ruilin He , Xiaoxi Mao , Changjie Fan , Minlie Huang