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Large language models (LLMs) such as ChatGPT have received immense interest for their general-purpose language understanding and, in particular, their ability to generate high-quality text or computer code. For many professions, LLMs…

计算与语言 · 计算机科学 2024-04-03 Simon Frieder , Julius Berner , Philipp Petersen , Thomas Lukasiewicz

Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Language Models (LLMs) can answer questions, write high-quality…

Large language models (LLMs) have received considerable attention recently due to their outstanding comprehension and reasoning capabilities, leading to great progress in many fields. The advancement of LLM techniques also offers promising…

系统与控制 · 电气工程与系统科学 2024-09-17 Hao Zhou , Chengming Hu , Ye Yuan , Yufei Cui , Yili Jin , Can Chen , Haolun Wu , Dun Yuan , Li Jiang , Di Wu , Xue Liu , Charlie Zhang , Xianbin Wang , Jiangchuan Liu

This paper explores the use of Large Language Models (LLMs) and in particular ChatGPT in programming, source code analysis, and code generation. LLMs and ChatGPT are built using machine learning and artificial intelligence techniques, and…

软件工程 · 计算机科学 2023-06-12 Ahmed R. Sadik , Antonello Ceravola , Frank Joublin , Jibesh Patra

Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite their notable performance in the general domain, LLMs have…

计算与语言 · 计算机科学 2025-01-23 Jingyuan Chen , Tao Wu , Wei Ji , Fei Wu

In traditional innovation practices, concept and IP generation are often iteratively integrated. Both processes demand an intricate understanding of advanced technical domain knowledge. Existing large language models (LLMs), while…

计算与语言 · 计算机科学 2025-04-09 Runtao Ren , Jian Ma , Jianxi Luo

Large Language Models (LLMs) generate responses to questions; however, their effectiveness is often hindered by sub-optimal quality of answers and occasional failures to provide accurate responses to questions. To address these challenges,…

计算与语言 · 计算机科学 2024-02-06 Liang Zhang , Katherine Jijo , Spurthi Setty , Eden Chung , Fatima Javid , Natan Vidra , Tommy Clifford

Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. Unlike conventional models, LLMs can adapt to new domains through prompt…

人工智能 · 计算机科学 2024-06-18 Ming Cheung

With the continuous development and change exhibited by large language model (LLM) technology, represented by generative pretrained transformers (GPTs), many classic scenarios in various fields have re-emerged with new opportunities. This…

信息检索 · 计算机科学 2024-10-22 Aakas Zhiyuli , Yanfang Chen , Xuan Zhang , Xun Liang

The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many researchers to propose their own LLM benchmarks. Noticing preliminary…

人工智能 · 计算机科学 2025-05-15 Timothy R. McIntosh , Teo Susnjak , Nalin Arachchilage , Tong Liu , Paul Watters , Malka N. Halgamuge

Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

人工智能 · 计算机科学 2024-04-10 Saikat Barua

Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis. To enable using context beyond limited context windows,…

人工智能 · 计算机科学 2024-02-13 Charles Packer , Sarah Wooders , Kevin Lin , Vivian Fang , Shishir G. Patil , Ion Stoica , Joseph E. Gonzalez

Despite the rapid progress of Large Language Models (LLMs), their application in agriculture remains limited due to the lack of domain-specific models, curated datasets, and robust evaluation frameworks. To address these challenges, we…

Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. They adapt to various styles and genres, producing content…

计算与语言 · 计算机科学 2025-07-08 Chinnappa Guggilla , Budhaditya Roy , Trupti Ramdas Chavan , Abdul Rahman , Edward Bowen

Large language models (LLMs) are often trained on extensive, temporally indiscriminate text corpora, reflecting the lack of datasets with temporal metadata. This approach is not aligned with the evolving nature of language. Conventional…

计算与语言 · 计算机科学 2024-04-30 Felix Drinkall , Eghbal Rahimikia , Janet B. Pierrehumbert , Stefan Zohren

Large language models (LLMs) have gained considerable attention for Artificial Intelligence Generated Content (AIGC), particularly with the emergence of ChatGPT. However, the direct adaptation of continuous speech to LLMs that process…

音频与语音处理 · 电气工程与系统科学 2023-08-28 Haibin Wu , Kai-Wei Chang , Yuan-Kuei Wu , Hung-yi Lee

Current large language models (LLMs) have proven useful for analyzing financial data, but most existing models, such as BloombergGPT and FinGPT, lack customization for specific user needs. In this paper, we address this gap by developing…

计算工程、金融与科学 · 计算机科学 2024-10-22 Felix Tian , Ajay Byadgi , Daniel Kim , Daochen Zha , Matt White , Kairong Xiao , Xiao-Yang Liu Yanglet

Generative large language models (LLMs) have become central to everyday life, producing human-like text across diverse domains. A growing body of research investigates whether these models also exhibit personality- and demographic-like…

计算与语言 · 计算机科学 2025-10-14 Dana Sotto Porat , Ella Rabinovich

The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative…

Topic modeling is a well-established technique for exploring text corpora. Conventional topic models (e.g., LDA) represent topics as bags of words that often require "reading the tea leaves" to interpret; additionally, they offer users…

计算与语言 · 计算机科学 2024-04-03 Chau Minh Pham , Alexander Hoyle , Simeng Sun , Philip Resnik , Mohit Iyyer