Paper Citation Record · LEDGER

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2601.06135.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2601.06135 v3

Coverage vector

measured 44 of 44 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-03T12:48:21.132186Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

44 of 44 outbound references displayed

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Outbound references

Observation bf2454f1-051c-46e8-b2ad-8680abc256f2 · outbound

This paper cites Defense Mapping Agency.Department of Defense World Geodetic System 1984: its definition and relationships with local geodetic systems, volume 8350.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Defense Mapping Agency.Department of Defense World Geodetic System 1984: its definition and relationships with local geodetic systems, volume 8350

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.121569Z

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Observation a91bf8ae-439a-4736-b89a-4ea3f0728e12 · outbound

This paper cites A genetic- based incremental local outlier factor algorithm for efficient data stream processing.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels A genetic- based incremental local outlier factor algorithm for efficient data stream processing

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.226603Z

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Observation bb0e5471-8920-4135-9944-ed35ce1989bc · outbound

This paper cites John Wiley & Sons, 2001.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels John Wiley & Sons, 2001

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.337910Z

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Observation ebe593f3-1744-4a6c-bb4d-1764f78cc225 · outbound

This paper cites A weighted k-nearest neighbor density estimate for geometric inference.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels A weighted k-nearest neighbor density estimate for geometric inference

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.449553Z

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Observation 143e119f-017f-4446-95f1-055d63850d12 · outbound

This paper cites Springer, 2006.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Springer, 2006

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.524871Z

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Observation 42c446e2-e3e7-4342-a954-08e9fe2727e4 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels On the Opportunities and Risks of Foundation Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.635124Z

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Observation 33e2c624-619a-44c8-9db2-05f56b68eb59 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.748297Z

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Observation 6ef96adf-b325-4ac9-82c8-45f96f8c6ee7 · outbound

This paper cites Anomaly detection: A survey.ACM computing surveys (CSUR), 41(3):1–58, 2009.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Anomaly detection: A survey.ACM computing surveys (CSUR), 41(3):1–58, 2009

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.845058Z

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Observation 06e5cb42-9ee8-4141-b28e-147c066ab817 · outbound

This paper cites Rethinking Attention with Performers.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Rethinking Attention with Performers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.888875Z

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Observation b37ac4b0-f702-4e0c-8c5c-34e9eb8a0836 · outbound

This paper cites Nearest neighbor pattern classification.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Nearest neighbor pattern classification

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:17.980118Z

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Observation b7760d37-1e8a-4c7b-b585-41a2f48ed7bb · outbound

This paper cites springer New York, 1978.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels springer New York, 1978

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.032138Z

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Observation 5276cc1d-e54b-493f-83a0-82a26b98fd40 · outbound

This paper cites Spatial data mining: A database approach.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Spatial data mining: A database approach

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.106700Z

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Observation 01bd73af-8c49-4fa5-b5bc-7473b2a95cbe · outbound

This paper cites Evaluating pattern matching queries for spatial databases.The VLDB Journal, 28(5):649–673, 2019.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Evaluating pattern matching queries for spatial databases.The VLDB Journal, 28(5):649–673, 2019

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.199355Z

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Observation 81f6c87e-3f57-4536-930f-3cf4f75145a1 · outbound

This paper cites Geographical information science.International journal of geographical information systems, 6(1):31–45, 1992.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Geographical information science.International journal of geographical information systems, 6(1):31–45, 1992

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.287963Z

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Observation f3505376-6c9d-4283-a54c-5ed7ddd6113e · outbound

This paper cites Exploration- based statistical learning for selecting kernel density estimates of spatial point patterns.Transactions in GIS, 29(2):e70051, 2025.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Exploration- based statistical learning for selecting kernel density estimates of spatial point patterns.Transactions in GIS, 29(2):e70051, 2025

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.367436Z

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Observation 5056156d-c5a0-4b9c-8951-4c671eba9492 · outbound

This paper cites Global positioning system: theory and practice.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Global positioning system: theory and practice

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.464919Z

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Observation d7ed17ca-9198-44df-ba55-e35b3f637f6f · outbound

This paper cites Product quantization for nearest neighbor search.IEEE transactions on pattern analysis and machine intelligence, 33(1):117–128, 2011.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Product quantization for nearest neighbor search.IEEE transactions on pattern analysis and machine intelligence, 33(1):117–128, 2011

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.541419Z

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Observation 0e52b211-4c11-4a5d-9d34-cff2924de8cd · outbound

This paper cites Billion-scale similarity search with gpus.IEEE Transactions on Big Data, 2017.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Billion-scale similarity search with gpus.IEEE Transactions on Big Data, 2017

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.597412Z

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Observation 6ca0aa33-8b12-4e35-8329-1584b8cbb318 · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 19

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Observation 83035ed1-5926-4f74-ba9a-6976319e98dc · outbound

This paper cites Trajectory clustering: a partition-and-group framework.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Trajectory clustering: a partition-and-group framework

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.787668Z

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Observation 24c919c2-e7bc-4bfb-b0fb-1b23737c6fcb · outbound

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Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.872928Z

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Observation e26cd5c3-2e3e-4585-b3c2-b2e8b76f1f36 · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 22

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Observation 5fd0e373-64f6-4dd1-b808-26ef0d5bac6e · outbound

This paper cites Data-driven geography.Geo- Journal, 80(4):449–461, 2015.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Data-driven geography.Geo- Journal, 80(4):449–461, 2015

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:18.991872Z

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Observation 91385a75-1c1d-4bbc-b383-52a1ea203b1e · outbound

This paper cites Knn-kernel based clustering for spatio-temporal database.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Knn-kernel based clustering for spatio-temporal database

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:19.062108Z

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Observation 71a6d7e8-5d8e-408d-87ef-f3ea43cf870d · outbound

This paper cites Continuous spatial query processing: A survey of safe region based techniques.ACM Computing Surveys (CSUR), 51(3):1–39, 2018.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Continuous spatial query processing: A survey of safe region based techniques.ACM Computing Surveys (CSUR), 51(3):1–39, 2018

Reference 25

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Observation a1f62096-8883-4deb-bf56-ed0ddae7a9b9 · outbound

This paper cites A pid-based knn query processing algorithm for spatial data.Sensors, 22(19):7651, 2022.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels A pid-based knn query processing algorithm for spatial data.Sensors, 22(19):7651, 2022

Reference 26

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Observation 03634608-9b38-4379-9e88-6b2835f83f60 · outbound

This paper cites John Wiley & Sons, 2015.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels John Wiley & Sons, 2015

Reference 27

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Observation 895ed481-2ab1-4bcd-bb4b-fd92a3f6e69c · outbound

This paper cites Benchmarking spatial big data.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Benchmarking spatial big data

Reference 28

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Observation 194649c9-0529-497a-b2ed-d6a60443b299 · outbound

This paper cites Springer Science & Business Media, 2007.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Springer Science & Business Media, 2007

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:19.537286Z

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Observation dee5cbde-d5fb-405c-aa89-7a93f2099cbe · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:19.694750Z

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Observation 79fb2809-8c85-4e28-8c70-b00c986afab4 · outbound

This paper cites Variable kernel density estimation.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Variable kernel density estimation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:19.847366Z

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Observation e88856df-9bc6-403e-92e6-0c39645234b2 · outbound

This paper cites Ancient lowland maya neighborhoods: Average nearest neighbor analysis and kernel density models, environments, and urban scale.PloS one, 17(11):e0275916, 2022.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Ancient lowland maya neighborhoods: Average nearest neighbor analysis and kernel density models, environments, and urban scale.PloS one, 17(11):e0275916, 2022

Reference 32

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Observation a303d1a9-33a2-4e25-a540-8eb8454fa14a · outbound

This paper cites Research on urban landscape accessibility assessment model based on gis and spatial analysis.GeoJournal, 90(2):67, 2025.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Research on urban landscape accessibility assessment model based on gis and spatial analysis.GeoJournal, 90(2):67, 2025

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.110695Z

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Observation 0820b7f5-738f-4350-ba00-223bff17fc50 · outbound

This paper cites Solution of incorrectly formulated problems and the regularization method.Sov Dok, 4:1035–1038, 1963.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Solution of incorrectly formulated problems and the regularization method.Sov Dok, 4:1035–1038, 1963

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.151904Z

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Observation 93c21dee-e2f3-49e2-bfa8-90d2381b4792 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.314764Z

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Observation 254cc779-77ef-41eb-acd6-8fac9e90de36 · outbound

This paper cites Scipy 1.0: fundamental algorithms for scientific computing in python.Nature methods, 17(3):261–272, 2020.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Scipy 1.0: fundamental algorithms for scientific computing in python.Nature methods, 17(3):261–272, 2020

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.447404Z

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Observation 5ee7e784-e320-4cd0-ab92-bcd2ec65ca28 · outbound

This paper cites Fast computation of multivariate kernel estimators.Journal of Computational and Graphical Statistics, 3(4):433–445, 1994.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Fast computation of multivariate kernel estimators.Journal of Computational and Graphical Statistics, 3(4):433–445, 1994

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.544745Z

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Observation 4f5625ba-87f0-465a-9b05-ff58a81ace5a · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 38

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Observation b17b8d67-5301-4913-93a1-9f33f19c8e88 · outbound

This paper cites Trajectory data mining: an overview.ACM Transactions on Intelligent Systems and Technology (TIST), 6(3):1–41, 2015.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Trajectory data mining: an overview.ACM Transactions on Intelligent Systems and Technology (TIST), 6(3):1–41, 2015

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:20.685713Z

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Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels coords": [],

Reference 40

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Observation 54fd60d4-39ae-4632-bd0c-ee66f7d6d89f · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 41

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Observation a863a3d3-9ccd-4984-8c3d-d339e340b85e · outbound

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Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 42

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Observation 381b1bab-c0b5-47c4-af38-f6136834aa36 · outbound

This paper cites an unresolved cited work.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Unresolved cited work

Reference 43

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Observation 62510ac6-f44a-47a9-bf3c-be9e99e0f1c0 · outbound

This paper cites These points often correspond to sharp maneuvers, abnormal motion, or sensor irregularities, and they serve as valuable markers for downstream analysis.

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels These points often correspond to sharp maneuvers, abnormal motion, or sensor irregularities, and they serve as valuable markers for downstream analysis

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:21.132186Z

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