Geode: A Zero-shot Geospatial Question-Answering Agent with Explicit Reasoning and Precise Spatio-Temporal Retrieval
Large language models (LLMs) have shown promising results in learning and contextualizing information from different forms of data. Recent advancements in foundational models, particularly those employing self-attention mechanisms, have significantly enhanced our ability to comprehend the semantics of diverse data types. One such area that could highly benefit from multi-modality is in understanding geospatial data, which inherently has multiple modalities. However, current Natural Language Processing (NLP) mechanisms struggle to effectively address geospatial queries. Existing pre-trained LLMs are inadequately equipped to meet the unique demands of geospatial data, lacking the ability to retrieve precise spatio-temporal data in real-time, thus leading to significantly reduced accuracy in answering complex geospatial queries. To address these limitations, we introduce Geode--a pioneering system designed to tackle zero-shot geospatial question-answering tasks with high precision using spatio-temporal data retrieval. Our approach represents a significant improvement in addressing the limitations of current LLM models, demonstrating remarkable improvement in geospatial question-answering abilities compared to existing state-of-the-art pre-trained models.
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringSimilar Papers 제목 키워드 기반
Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?
Sentence transformers are language models designed to perform semantic search. This study investigates the capacity of sentence transformers, fine-tuned on general question-answering datasets for asymmetric semantic sear…
Question AnsweringRecommendation SystemsSentenceBenchmarking Geospatial Question Answering Engines using the Dataset GeoQuestions1089
We present the dataset GeoQuestions1089 for benchmarking geospatial question answering engines. GeoQuestions1089 is the largest such dataset available presently and it contains 1089 questions, their corresponding GeoSPA…
BenchmarkingKnowledge Base Question AnsweringQuestion AnsweringGeoDecoder: Empowering Multimodal Map Understanding
This paper presents GeoDecoder, a dedicated multimodal model designed for processing geospatial information in maps. Built on the BeitGPT architecture, GeoDecoder incorporates specialized expert modules for image and tex…
Feature EngineeringTemplate-Based Question Answering over Linked Geospatial Data
Large amounts of geospatial data have been made available recently on the linked open data cloud and the portals of many national cartographic agencies (e.g., OpenStreetMap data, administrative geographies of various cou…
Question AnsweringDocPrompt: Large-scale continue pretrain for zero-shot and few-shot document question answering
In this paper, we propose Docprompt for document question answering tasks with powerful zero-shot and few-shot performance. We proposed a novel weakly supervised data generation method, a novel multl-stage training metho…
Question Answering