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With the emerging trend of GPT models, we have established a framework called AutoML-GPT that integrates a comprehensive set of tools and libraries. This framework grants users access to a wide range of data preprocessing techniques,…

机器学习 · 计算机科学 2023-09-06 Yun-Da Tsai , Yu-Che Tsai , Bo-Wei Huang , Chun-Pai Yang , Shou-De Lin

Graph Databases (Graph DB) find extensive application across diverse domains such as finance, social networks, and medicine. Yet, the translation of Natural Language (NL) into the Graph Query Language (GQL), referred to as NL2GQL, poses…

计算与语言 · 计算机科学 2024-09-06 Yuanyuan Liang , Keren Tan , Tingyu Xie , Wenbiao Tao , Siyuan Wang , Yunshi Lan , Weining Qian

Large language models (LLMs) have shown the potential of revolutionizing natural language processing tasks in diverse domains, sparking great interest in finance. Accessing high-quality financial data is the first challenge for financial…

统计金融 · 定量金融 2025-11-18 Hongyang Yang , Xiao-Yang Liu , Christina Dan Wang

In this article, we evaluate four Large Language Models (LLMs) and their effectiveness at retrieving data within a specialized Retrieval-Augmented Generation (RAG) system, using a comprehensive food composition database. Our method is…

计算与语言 · 计算机科学 2026-03-12 Maks Požarnik Vavken , Matevž Ogrinc , Tome Eftimov , Barbara Koroušić Seljak

The rapid advancement of large language models (LLMs) such as GPT-3, PaLM, and Llama has significantly transformed natural language processing, showcasing remarkable capabilities in understanding and generating language. However, a…

计算与语言 · 计算机科学 2026-05-15 Yifan Zhang

Large language models (LLMs) often lack specialized knowledge for complex bioinformatics applications. We present a reproducible pipeline for fine-tuning LLMs on specialized bioinformatics data, demonstrated through two use cases: PRSGPT,…

计算与语言 · 计算机科学 2026-01-21 Muhammad Muneeb , David B. Ascher

The widespread adoption of REST APIs, coupled with their growing complexity and size, has led to the need for automated REST API testing tools. Current tools focus on the structured data in REST API specifications but often neglect valuable…

软件工程 · 计算机科学 2024-01-31 Myeongsoo Kim , Tyler Stennett , Dhruv Shah , Saurabh Sinha , Alessandro Orso

Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and…

人工智能 · 计算机科学 2023-07-12 Jiayan Guo , Lun Du , Hengyu Liu , Mengyu Zhou , Xinyi He , Shi Han

Over the last few years, large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP) that fundamentally transform research and developments in the field. ChatGPT represents one of the…

As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grounded in science communication research, to assess LLM…

Large Language Models (LLMs) have shown versatility in various Natural Language Processing (NLP) tasks, including their potential as effective question-answering systems. However, to provide precise and relevant information in response to…

计算与语言 · 计算机科学 2024-09-09 Sriram Veturi , Saurabh Vaichal , Reshma Lal Jagadheesh , Nafis Irtiza Tripto , Nian Yan

Large Language Models (LLMs) have demonstrated superior abilities in tasks such as chatting, reasoning, and question-answering. However, standard LLMs may ignore crucial paralinguistic information, such as sentiment, emotion, and speaking…

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

Despite significant progress in multimodal large language models (MLLMs), their performance on complex, multi-page document comprehension remains inadequate, largely due to the lack of high-quality, document-level datasets. While current…

计算机视觉与模式识别 · 计算机科学 2025-07-22 Yuchen Duan , Zhe Chen , Yusong Hu , Weiyun Wang , Shenglong Ye , Botian Shi , Lewei Lu , Qibin Hou , Tong Lu , Hongsheng Li , Jifeng Dai , Wenhai Wang

Efficient and sustainable crop production process management is crucial to meet the growing global demand for food, fuel, and feed while minimizing environmental impacts. Traditional crop management practices, often developed through…

系统与控制 · 电气工程与系统科学 2024-10-15 Dong Chen , Yanbo Huang

Tool-augmented large language models (LLMs) have achieved remarkable progress in tackling a broad range of tasks. However, existing methods are mainly restricted to specifically designed tools and fail to fulfill complex instructions,…

计算与语言 · 计算机科学 2023-08-29 Yifan Song , Weimin Xiong , Dawei Zhu , Wenhao Wu , Han Qian , Mingbo Song , Hailiang Huang , Cheng Li , Ke Wang , Rong Yao , Ye Tian , Sujian Li

Knowledge graphs provide structured and reliable information for many real-world applications, motivating increasing interest in combining large language models (LLMs) with graph-based retrieval to improve factual grounding. Recent…

人工智能 · 计算机科学 2026-04-16 Yuchen Ying , Weiqi Jiang , Tongya Zheng , Yu Wang , Shunyu Liu , Kaixuan Chen , Mingli Song

The rapid growth of the financial sector and the rising focus on Environmental, Social, and Governance (ESG) considerations highlight the need for advanced NLP tools. However, open-source LLMs proficient in both finance and ESG domains…

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 demonstrated remarkable capabilities in many real-world applications. Nonetheless, LLMs are often criticized for their tendency to produce hallucinations, wherein the models fabricate incorrect statements…

计算与语言 · 计算机科学 2024-06-05 Qinggang Zhang , Junnan Dong , Hao Chen , Daochen Zha , Zailiang Yu , Xiao Huang