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The integration of Large Language Models (LLMs) like ChatGPT into the workflows of geotechnical engineering has a high potential to transform how the discipline approaches problem-solving and decision-making. This paper delves into the…

Large Language Models(LLMs) trained on large data sets came into prominence in 2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from OpenAI have been released. These models perform well on diverse tasks and…

人机交互 · 计算机科学 2024-07-23 Abdullahi Saka , Ridwan Taiwo , Nurudeen Saka , Babatunde Salami , Saheed Ajayi , Kabiru Akande , Hadi Kazemi

Programming reliability algorithms is crucial for risk assessment in geotechnical engineering. This study explores the possibility of automating and accelerating this task using Generative AI based on Large Language Models (LLMs).…

应用统计 · 统计学 2025-06-25 Atma Sharma , Jie Zhang , Meng Lu , Shuangyi Wu , Baoxiang Li

The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, often with an emphasis on high-level opportunities and…

人机交互 · 计算机科学 2023-06-27 Philippe J. Giabbanelli

Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit…

计算与语言 · 计算机科学 2023-10-20 Katikapalli Subramanyam Kalyan

The rapid advancement of large language models (LLMs) is transforming opportunities in geotechnical engineering, where workflows rely on complex, text-rich data. While general-purpose LLMs demonstrate strong reasoning capabilities, their…

人工智能 · 计算机科学 2025-12-01 Lei Fan , Fangxue Liu , Cheng Chen

Large language models (LLMs) have shown remarkable capabilities across a broad range of tasks involving question answering and the generation of coherent text and code. Comprehensively understanding the strengths and weaknesses of LLMs is…

计算与语言 · 计算机科学 2023-06-02 Jonathan Roberts , Timo Lüddecke , Sowmen Das , Kai Han , Samuel Albanie

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

In this paper, we explore the challenges inherent to Large Language Models (LLMs) like GPT-4, particularly their propensity for hallucinations, logic mistakes, and incorrect conclusions when tasked with answering complex questions. The…

计算与语言 · 计算机科学 2023-12-22 Xiang Li , Haoran Tang , Siyu Chen , Ziwei Wang , Anurag Maravi , Marcin Abram

With the increasing impacts of climate change, there is a growing demand for accessible tools that can provide reliable future climate information to support planning, finance, and other decision-making applications. Large language models…

机器学习 · 计算机科学 2024-11-22 Yang Wang , Hassan A. Karimi

Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate…

软件工程 · 计算机科学 2025-05-21 Md Asraful Haque

Large Language Models (LLMs) have shown great potential in solving complex problems in various fields, including oil and gas engineering and other industrial engineering disciplines like factory automation, PLC programming etc. However,…

计算与语言 · 计算机科学 2023-04-28 Oluwatosin Ogundare , Srinath Madasu , Nathanial Wiggins

The usefulness of Large Language Models (LLM) is being continuously tested in various fields. However, their intrinsic linguistic characteristic is still one of the limiting factors when applying these models to exact sciences. In this…

人工智能 · 计算机科学 2024-09-24 Jonathan Paul Driemeyer Brown , Tiago Oliveira Weber

This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (NLP) tasks. We provide discussions and insights into the…

计算与语言 · 计算机科学 2023-04-28 Jingfeng Yang , Hongye Jin , Ruixiang Tang , Xiaotian Han , Qizhang Feng , Haoming Jiang , Bing Yin , Xia Hu

Coverage of ChatGPT-style large language models (LLMs) in the media has focused on their eye-catching achievements, including solving advanced mathematical problems and reaching expert proficiency in medical examinations. But the gradual…

计算机与社会 · 计算机科学 2024-03-26 Djavan De Clercq , Elias Nehring , Harry Mayne , Adam Mahdi

Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series. In these lectures, written for readers with a background in mathematics or…

计算与语言 · 计算机科学 2023-10-09 Michael R. Douglas

Significant advancements have been made in one of the most critical branches of artificial intelligence: natural language processing (NLP). These advancements are exemplified by the remarkable success of OpenAI's GPT-3.5/4 and the recent…

材料科学 · 物理学 2025-04-22 Zongrui Pei , Junqi Yin , Jiaxin Zhang

The startling success of ChatGPT and other large language models (LLMs) using transformer-based generative neural network architecture in applications such as natural language processing and image synthesis has many researchers excited…

人工智能 · 计算机科学 2024-11-05 Venkat Venkatasubramanian , Arijit Chakraborty

Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

计算与语言 · 计算机科学 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntactically correct content. Despite challenges like biases and…

计算与语言 · 计算机科学 2025-08-04 Alper Yaman , Jannik Schwab , Christof Nitsche , Abhirup Sinha , Marco Huber
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