mlsanityData to 14 Oct 2026

Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions

arXiv 2105.09392 ↗First posted 19 May 2021cs.CL cs.AIcited by 24

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Abstract (arXiv)

As an important part of Artificial Intelligence (AI), Question Answering (QA) aims at generating answers to questions phrased in natural language. While there has been substantial progress in open-domain question answering, QA systems are still struggling to answer questions which involve geographic entities or concepts and that require spatial operations. In this paper, we discuss the problem of geographic question answering (GeoQA). We first investigate the reasons why geographic questions are difficult to answer by analyzing challenges of geographic questions. We discuss the uniqueness of geographic questions compared to general QA. Then we review existing work on GeoQA and classify them by the types of questions they can address. Based on this survey, we provide a generic classification framework for geographic questions. Finally, we conclude our work by pointing out unique future research directions for GeoQA.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). Builds on 26 of its 75 references that are in the map. First posted on arXiv 19 May 2021.

Builds on

26 of 75 references.

References · 26

  1. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,148
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  3. 2015VQA: Visual Question Answeringcited by 2,506
  4. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  5. 2018CoQA: A Conversational Question Answering Challengecited by 683
  6. 2016Key-Value Memory Networks for Directly Reading Documentscited by 223
  7. 2020RSVQA: Visual Question Answering for Remote Sensing Datacited by 203
  8. 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 168
  9. 2020Answering Complex Open-Domain Questions with Multi-Hop Dense Retrievalcited by 162
  10. 2019End-to-End Open-Domain Question Answering with BERTserinicited by 152
  11. 2019Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answeringcited by 147
  12. 2019Presence-Only Geographical Priors for Fine-Grained Image Classificationcited by 109
14 more
  1. 2016Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervisioncited by 103
  2. 2020Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cellscited by 90
  3. 2018Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsingcited by 57
  4. 2019Improving Question Answering over Incomplete KBs with Knowledge-Aware Readercited by 37
  5. 2020SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Liftingcited by 23
  6. 2019GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Levelcited by 17
  7. 2016Simple Question Answering by Attentive Convolutional Neural Networkcited by 12
  8. 2020Template-Based Question Answering over Linked Geospatial Datacited by 12
  9. 2020Joint Spatio-Textual Reasoning for Answering Tourism Questionscited by 9
  10. 2019Large Scale Question Answering using Tourism Datacited by 4
  11. 2018Encoding Spatial Relations from Natural Languagecited by 3
  12. 2018POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Datasetcited by 3
  13. 2020Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Onlinecited by 2
  14. 2017Learning to Organize Knowledge and Answer Questions with N-Gram Machinescited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 6; 2024: 7; 2025: 5; 2026: 4.

24 papers.

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  1. 2023RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensingcited by 151
  2. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  3. 2021A Review of Location Encoding for GeoAI: Methods and Applicationscited by 54
  4. 2023AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiologycited by 34
  5. 2024TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learningcited by 31
  6. 2024CityGPT: Empowering Urban Spatial Cognition of Large Language Modelscited by 30
  7. 2024CityBench: Evaluating the Capabilities of Large Language Models for Urban Taskscited by 27
  8. 2022Towards General-Purpose Representation Learning of Polygonal Geometriescited by 22
  9. 2023Multimodality of AI for Education: Towards Artificial General Intelligencecited by 21
  10. 2025MapQA: Open-domain Geospatial Question Answering on Map Datacited by 15
  11. 2025Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questionscited by 13
  12. 2025A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Sciencecited by 12
12 more
  1. 2024PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graphcited by 10
  2. 2023AGI for Agriculturecited by 9
  3. 2024Evaluation of Code LLMs on Geospatial Code Generationcited by 8
  4. 2023EVKG: An Interlinked and Interoperable Electric Vehicle Knowledge Graph for Smart Transportation Systemcited by 6
  5. 2025Towards a Barrier-free GeoQA Portal: Natural Language Interaction with Geospatial Data Using Multi-Agent LLMs and Semantic Searchcited by 3
  6. 2024Location Aware Modular Biencoder for Tourism Question Answeringcited by 2
  7. 2025OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Modelscited by 2
  8. 2024The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphscited by 1
  9. 2026UrbanGraphEmbeddings: Learning and Evaluating Spatially Grounded Multimodal Embeddings for Urban Sciencecited by 1
  10. 2026Much of Geospatial Web Search Is Beyond Traditional GIScited by 0
  11. 2026Geo-Spatial Concept Probing of Large Language Models: Abstraction, Compositionality, and Groundingcited by 0
  12. 2026GeoBenchLLM: A Comprehensive Benchmark for Evaluating LLMs on Geo-Related Taskscited by 0