AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models | Paper Citation Record

Observation e7ee7fcc-0bf4-4b52-b584-633d9ecefc45 · outbound

This paper cites Competition-level code generation with alphacode.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Competition-level code generation with alphacode

Reference 1

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Observation 21d9e228-935a-4929-be56-aca49e2afad2 · outbound

This paper cites Learning to code or coding to learn? A systematic review.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Learning to code or coding to learn? A systematic review

Reference 2

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Observation 6852871f-bc18-4dbb-8951-7c3d2456b344 · outbound

This paper cites An overview of transaction logic.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models An overview of transaction logic

Reference 3

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Observation 2f961f4b-8ea2-4143-b955-cae05701e849 · outbound

This paper cites A Survey on Large Language Models for Code Generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models A Survey on Large Language Models for Code Generation

Reference 4

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Observation c9776c2c-0f01-4b27-876a-7eced72adde7 · outbound

This paper cites A review on code generation with llms: Application and evaluation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models A review on code generation with llms: Application and evaluation

Reference 5

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Observation 1b94541c-aceb-41b9-8396-f980da2581ba · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 6

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Observation badf4976-6236-4b50-993e-7ec00ea9bc87 · outbound

This paper cites Qwen2.5-Coder Technical Report.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Qwen2.5-Coder Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:30:40.646718Z

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Observation 4e67a9d3-63c2-4544-8d89-0613fb39d9a8 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Code Llama: Open Foundation Models for Code

Reference 8

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Observation 350c8796-3c60-4851-aaac-59f96e403240 · outbound

This paper cites Code Hallucination.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Code Hallucination

Reference 9

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Observation a30f781a-52e3-4d7f-b84a-9143902622f5 · outbound

This paper cites HumanEval on Latest GPT Models -- 2024.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models HumanEval on Latest GPT Models -- 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T20:30:40.660730Z

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Observation a955b216-27c0-4ebc-9550-e3066daeeb7d · outbound

This paper cites HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation

Reference 11

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Observation 1e02ed5a-cbfa-4f32-9bbc-59306137a60a · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 12

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Observation 3d369a85-4f77-4f3b-b235-d008f258d5ba · outbound

This paper cites Bioconductor: open software development for computational biology and bioinformatics.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Bioconductor: open software development for computational biology and bioinformatics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.809271Z

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Observation 63c47c98-d990-4036-b02d-8f74916862a2 · outbound

This paper cites Computational finance using QuantLib-Python.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Computational finance using QuantLib-Python

Reference 14

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This paper cites Orchestrating high-throughput genomic analysis with Bioconductor.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Orchestrating high-throughput genomic analysis with Bioconductor

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.779759Z

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Observation 65048d9d-e354-412a-976c-3e6b4081afab · outbound

This paper cites Orchestrating single -cell analysis with Biocon ductor.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Orchestrating single -cell analysis with Biocon ductor

Reference 16

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Observation 3ac7ec3e-5f14-4e0c-88b1-426507c64c11 · outbound

This paper cites Domain -specific language techniques for visual computing: a comprehensive study.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Domain -specific language techniques for visual computing: a comprehensive study

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.751741Z

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Observation 02ff78b6-0b84-4580-82f6-ee401bb72694 · outbound

This paper cites On the effectiveness of large language models in domain -specific code generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models On the effectiveness of large language models in domain -specific code generation

Reference 18

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Observation a2789195-58e8-4ed7-88d4-c4933ffc4585 · outbound

This paper cites Extracting land cover data using GEE: A review of the classification indices.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Extracting land cover data using GEE: A review of the classification indices

Reference 19

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Observation 7e0afb1b-39ba-4f65-baa1-8cb1711b5ecc · outbound

This paper cites Google Earth Engine for geo-big data ap plications: A meta-analysis and systematic review.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Google Earth Engine for geo-big data ap plications: A meta-analysis and systematic review

Reference 20

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Observation a2f1bae3-73b8-48ad-b934-ef095f12ac1c · outbound

This paper cites Tangible User Interfaces (TUIs): a novel paradigm for GIS.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Tangible User Interfaces (TUIs): a novel paradigm for GIS

Reference 21

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Observation 0428972e-ca7b-4a0c-b0e7-b48404561dc5 · outbound

This paper cites Progress and trends in the application of Google Earth and Google Earth Engine.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Progress and trends in the application of Google Earth and Google Earth Engine

Reference 22

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Observation 14eb8167-81ca-4baa-9e77-65c217b34544 · outbound

This paper cites Google earth engine applications.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Google earth engine applications

Reference 23

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Observation 7768828e-a057-4b84-bca1-ad5441b252bd · outbound

This paper cites GeoCode -GPT: A large language model for geospatial code generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GeoCode -GPT: A large language model for geospatial code generation

Reference 24

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Observation c334f4f9-f099-4c32-a340-07cf845a81f8 · outbound

This paper cites GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models

Reference 25

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This paper cites Google Earth Engine and artificial intelligence (AI): a comprehensive review.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Google Earth Engine and artificial intelligence (AI): a comprehensive review

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.628656Z

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Observation b2714ddd-7a31-4371-ad4b-5055f2c7e1bf · outbound

This paper cites Can Large Language Models Generate Geospatial Code?.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Can Large Language Models Generate Geospatial Code?

Reference 27

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This paper cites Evaluation of Code LLMs on Geospatial Code Generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Evaluation of Code LLMs on Geospatial Code Generation

Reference 28

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This paper cites Chain-of-Programming (CoP) : Empowering Large Language Models for Geospatial Code Generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Chain-of-Programming (CoP) : Empowering Large Language Models for Geospatial Code Generation

Reference 29

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This paper cites GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks

Reference 30

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This paper cites Geo-FuB: A Method for Constructing an Operator-Function Knowledge Base for Geospatial Code Generation Tasks Using Large Language Models.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Geo-FuB: A Method for Constructing an Operator-Function Knowledge Base for Geospatial Code Generation Tasks Using Large Language Models

Reference 31

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This paper cites Big Data and cloud computing: innovation opportunit ies and challenges.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Big Data and cloud computing: innovation opportunit ies and challenges

Reference 32

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c3b57e27-9b80-4e78-b064-71028a6101ce · outbound

This paper cites Evaluating large language models on geospatial tasks: a multiple geospatial task benchmarking study.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Evaluating large language models on geospatial tasks: a multiple geospatial task benchmarking study

Reference 33

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This paper cites GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.582431Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 83a3783b-cb2c-479c-bd19-41cf37648127 · outbound

This paper cites An overview of the Canada geographic information system (CGIS); Lands Directorate Environment Canada Ottawa, ON, Canada: 1980.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models An overview of the Canada geographic information system (CGIS); Lands Directorate Environment Canada Ottawa, ON, Canada: 1980

Reference 35

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Observation f812d080-7aea-4815-9b42-a6bc77c34633 · outbound

This paper cites GRASS GIS: A multi -purpose open source GIS.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GRASS GIS: A multi -purpose open source GIS

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.549749Z

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Observation ad83cc4c-d473-4fae-9b09-626f3da00803 · outbound

This paper cites GISc ript: Towards an interoperable geospatial scripting language for GIS programming.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GISc ript: Towards an interoperable geospatial scripting language for GIS programming

Reference 37

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da9bae2c-affe-4256-bc72-7c501dee528e · outbound

This paper cites Open geospatial software and data: A review of the current state and a perspective into the future.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Open geospatial software and data: A review of the current state and a perspective into the future

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.520120Z

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Observation 868b8e1f-5db2-4349-93ae-aab508fa23b7 · outbound

This paper cites Code-literacy for GIS librarians: A discussion of languages, use cases, and competencies.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Code-literacy for GIS librarians: A discussion of languages, use cases, and competencies

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.503766Z

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Observation 6b3fea3d-dcb9-421e-b464-5e4d5de6728f · outbound

This paper cites Show me the code: spatial analysis and open source.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Show me the code: spatial analysis and open source

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.489216Z

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Observation 7bad90eb-928a-418b-a6f7-4df95b169e76 · outbound

This paper cites Open geospatial analytics with PySAL.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Open geospatial analytics with PySAL

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.473985Z

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Observation ae9e6ae8-cd0b-40f1-a334-8508a19c6a0e · outbound

This paper cites Validation of GCC optimizers through trace generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Validation of GCC optimizers through trace generation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.459772Z

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Observation 62b26b9a-53d9-4f33-8f4f-555d69f5fab8 · outbound

This paper cites An empirical evaluation of Lex/Yacc and ANTLR parser generation tools.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models An empirical evaluation of Lex/Yacc and ANTLR parser generation tools

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.445299Z

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Observation d72efff2-7fb0-46c1-964e-9485315fab93 · outbound

This paper cites Template-based model generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Template-based model generation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.430856Z

Source-reported events for the cited work

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Observation 5fd38bfd-d110-4ad3-bcac-582639f7e169 · outbound

This paper cites Systematic mapping study of template-based code generation.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Systematic mapping study of template-based code generation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.415824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06adcc47-0cf6-4012-928c-37d9bdadcda8 · outbound

This paper cites DeepCoder: Learning to Write Programs.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models DeepCoder: Learning to Write Programs

Reference 46

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Observation e3078a68-1bd5-4e6a-a81a-e2034b7a5fab · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 47

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Observation 39fa9a0b-8cd7-4ff0-9061-e8b5ff9581ef · outbound

This paper cites code2seq: Generating Sequences from Structured Representations of Code.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models code2seq: Generating Sequences from Structured Representations of Code

Reference 48

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Observation 9d2ce6f0-6b93-448a-bc9a-786b904594ed · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 49

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Observation bc2a6f90-a0ad-4c1a-886a-a519ace47d26 · outbound

This paper cites Github copilot ai pair programmer: Asset or liability? Journal of Systems and Software 2023, 203, 111734.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Github copilot ai pair programmer: Asset or liability? Journal of Systems and Software 2023, 203, 111734

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.399543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dd2b5dc2-58e2-489f-afd3-369d41aa740a · outbound

This paper cites A GPT-enhanced framework on knowledge extraction and reuse for geographic analysis models in Google Earth Engine.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models A GPT-enhanced framework on knowledge extraction and reuse for geographic analysis models in Google Earth Engine

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.383239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3ca78ac5-7dbd-47a5-b17f-fc62d1ec08b8 · outbound

This paper cites Large Language Models Meet NL2Code: A Survey.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Large Language Models Meet NL2Code: A Survey

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T20:30:40.849568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 781d9adb-3614-41f7-a0d3-7d799a477e8e · outbound

This paper cites MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.367144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f6e899fe-214f-484e-bb04-9b9136a6006f · outbound

This paper cites ShapefileGPT: A Multi-Agent Large Language Model Framework for Automated Shapefile Processing.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models ShapefileGPT: A Multi-Agent Large Language Model Framework for Automated Shapefile Processing

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:30:40.949777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9700f90-bc1c-4e63-af3b-6a778783803a · outbound

This paper cites GIS Copilot: towards an autonomous GIS agent for spatial analysis.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GIS Copilot: towards an autonomous GIS agent for spatial analysis

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.350179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 249b54ec-dca9-4dff-9bd7-5ecf5b62740e · outbound

This paper cites A Survey on Evaluating Large Language Models in Code Generation Tasks.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models A Survey on Evaluating Large Language Models in Code Generation Tasks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T20:30:40.867685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a5a280d-b243-449e-b998-ebe8e640d274 · outbound

This paper cites Are static analysis violations really fixed? a closer look at realistic usage of sonarqube.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Are static analysis violations really fixed? a closer look at realistic usage of sonarqube

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.333304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05bab65e-85ea-4640-841d-e040d1bb0d7e · outbound

This paper cites Enhancing Code Readability through Automated Consistent Formatting.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Enhancing Code Readability through Automated Consistent Formatting

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.317981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 92c0e680-8a62-41b8-a7b3-b4de120905dc · outbound

This paper cites -S.; Khan, F.S.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models -S.; Khan, F.S

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.302461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eada2746-17e5-491a-af70-9665a6b4cc6e · outbound

This paper cites Remote sensing platforms and sensors: A survey.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Remote sensing platforms and sensors: A survey

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.287213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d327d9b8-c762-43ef-a9e0-c1e35e7197e8 · outbound

This paper cites Automating Geospatial Analysis Workflows Using ChatGPT-4.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models Automating Geospatial Analysis Workflows Using ChatGPT-4

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:30:41.271319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers