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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…

Computation and Language · Computer Science 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…

Machine Learning · Computer Science 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…

Computation and Language · Computer Science 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…

Computer Vision and Pattern Recognition · Computer Science 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…

Artificial Intelligence · Computer Science 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…

Artificial Intelligence · Computer Science 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…

Computation and Language · Computer Science 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…

Artificial Intelligence · Computer Science 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…

Computation and Language · Computer Science 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,…

Computation and Language · Computer Science 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…

Machine Learning · Computer Science 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…

Computation and Language · Computer Science 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…

Computation and Language · Computer Science 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…

Computation and Language · Computer Science 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'…

Artificial Intelligence · Computer Science 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…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Chenjiao Tan , Qian Cao , Yiwei Li , Jielu Zhang , Xiao Yang , Huaqin Zhao , Zihao Wu , Zhengliang Liu , Hao Yang , Nemin Wu , Tao Tang , Xinyue Ye , Lilong Chai , Ninghao Liu , Changying Li , Lan Mu , Tianming Liu , Gengchen Mai

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…

Computation and Language · Computer Science 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…

Computation and Language · Computer Science 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.…

Computation and Language · Computer Science 2024-07-12 Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti
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