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相关论文: GPT4GEO: How a Language Model Sees the World's Geo…

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Despite the impressive performance of Large Language Models (LLM) for various natural language processing tasks, little is known about their comprehension of geographic data and related ability to facilitate informed geospatial…

计算与语言 · 计算机科学 2023-10-23 Prabin Bhandari , Antonios Anastasopoulos , Dieter Pfoser

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) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have demonstrated the ability to answer generic questions, such…

计算与语言 · 计算机科学 2024-11-13 Pasquale Balsebre , Weiming Huang , Gao Cong

Multimodal large language models (MLLMs) have shown remarkable capabilities across a broad range of tasks but their knowledge and abilities in the geographic and geospatial domains are yet to be explored, despite potential wide-ranging…

计算机视觉与模式识别 · 计算机科学 2024-01-17 Jonathan Roberts , Timo Lüddecke , Rehan Sheikh , Kai Han , Samuel Albanie

Large Language Models (LLMs) are increasingly deployed in applications that interact with the physical world, such as navigation, robotics, or mapping, making robust geospatial reasoning a critical capability. Despite that, LLMs' ability to…

人工智能 · 计算机科学 2026-02-19 Thinh Hung Truong , Jey Han Lau , Jianzhong Qi

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

Large language models (LLMs) show remarkable capabilities across a variety of tasks. Despite the models only seeing text in training, several recent studies suggest that LLM representations implicitly capture aspects of the underlying…

计算与语言 · 计算机科学 2024-04-16 Yutaro Yamada , Yihan Bao , Andrew K. Lampinen , Jungo Kasai , Ilker Yildirim

We explore the geospatial reasoning capabilities of Large Language Models (LLMs), specifically, whether LLMs can read road network maps and perform navigation. We frame trajectory recovery as a proxy task, which requires models to…

人工智能 · 计算机科学 2025-10-03 Thinh Hung Truong , Jey Han Lau , Jianzhong Qi

Large Language Models (LLMs) inherently carry the biases contained in their training corpora, which can lead to the perpetuation of societal harm. As the impact of these foundation models grows, understanding and evaluating their biases…

计算与语言 · 计算机科学 2024-10-08 Rohin Manvi , Samar Khanna , Marshall Burke , David Lobell , Stefano Ermon

The widespread adoption of large language models (LLMs), such as OpenAI's ChatGPT, could revolutionize various industries, including geotechnical engineering. However, GPT models can sometimes generate plausible-sounding but false outputs,…

计算与语言 · 计算机科学 2023-06-22 Krishna Kumar

Large Language Models (LLMs) have demonstrated unprecedented capabilities across various natural language processing tasks. Their ability to process and generate viable text and code has made them ubiquitous in many fields, while their…

机器学习 · 计算机科学 2025-05-13 Stef De Sabbata , Stefano Mizzaro , Kevin Roitero

In recent years, groundbreaking advancements in natural language processing have culminated in the emergence of powerful large language models (LLMs), which have showcased remarkable capabilities across a vast array of domains, including…

计算与语言 · 计算机科学 2023-12-11 Microsoft Research AI4Science , Microsoft Azure Quantum

Large Language Models (LLMs) are known for their remarkable ability to generate synthesized 'knowledge', such as text documents, music, images, etc. However, there is a huge gap between LLM's and human capabilities for understanding…

计算与语言 · 计算机科学 2024-08-14 Vladimir Cherkassky , Eng Hock Lee

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

Large Language Models (LLMs) have shown impressive capabilities across a wide variety of tasks. However, they still face challenges with long-horizon planning. To study this, we propose path planning tasks as a platform to evaluate LLMs'…

人工智能 · 计算机科学 2024-06-24 Mohamed Aghzal , Erion Plaku , Ziyu Yao

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we…

The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabilities of GPT-4V in the realms of geography, environmental…

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

Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation across various domains, including medicine. We present a comprehensive evaluation of GPT-4, a state-of-the-art LLM, on…

计算与语言 · 计算机科学 2023-04-13 Harsha Nori , Nicholas King , Scott Mayer McKinney , Dean Carignan , Eric Horvitz

Large Language Models (LLMs) have revolutionized the field of Natural Language Processing thanks to their ability to reuse knowledge acquired on massive text corpora on a wide variety of downstream tasks, with minimal (if any) tuning steps.…

计算与语言 · 计算机科学 2024-07-12 Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti
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