{"as_of":"2026-08-08T07:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fcee02f12717df3d4366095b20155ee3e3de7933d4ce0397594378345e19360b","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:33:20.752374Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T10:17:01.611458Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":"2003.00824","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-07-10T10:17:01.611458Z","title":"Multi-scale representation learning for spatial feature distributions using grid cells","venue":"cs.CV","work_id":"bdf5e9f6-17c8-4e85-834f-b0702c579409","year":2020},"citing_paper":{"arxiv_id":"2503.16683","last_updated":"2026-04-20T21:20:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-20T19:59:39Z","title":"GAIR: Location-Aware Self-Supervised Contrastive Pre-Training with Geo-Aligned Implicit Representations","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-22T22:41:00.027266Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2503.16683"},"observation_digest":"sha256:56d5839fbd4346592be993b06793d8f99da80eef6d7dbcbb6bf378fe6d92c07c","observation_id":"acaa15c7-2248-4388-99d7-32002de6c159","resolution":{"observed_at":"2026-05-22T22:42:13.423237Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-07T10:33:20.752374Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.05016","last_updated":"2025-06-05T13:22:47Z","snapshot_observed_at":"2026-08-08T00:10:40.174724Z","submitted_at":"2025-06-05T13:22:47Z","title":"Multi-Point Proximity Encoding For Vector-Mode Geospatial Machine Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T10:33:20.752374Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2506.05016"},"observation_digest":"sha256:8f3f326ee8a982936126001996d8d5003e491c74feba5603844d760f9346ca88","observation_id":"536b21ef-99e5-4946-94ed-0c2510d5c7d6","resolution":{"observed_at":"2026-08-07T10:33:20.752374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-07T00:13:48.905138Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.17302","last_updated":"2025-06-17T22:09:48Z","snapshot_observed_at":"2026-08-07T00:07:18.734058Z","submitted_at":"2025-06-17T22:09:48Z","title":"Fine-Scale Soil Mapping in Alaska with Multimodal Machine Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:48.905138Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2506.17302"},"observation_digest":"sha256:63a3b601e40c59b291a0d4d244ac1065861ac2f16ee99755a5257ddf4f28a62b","observation_id":"79fd5f4e-da1e-4a1b-875f-98f24338982c","resolution":{"observed_at":"2026-08-07T00:13:48.905138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-06T20:25:36.285685Z","title":"Multi-scale representation learning for spatial feature distributions using grid cells","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2507.03062","last_updated":"2025-07-03T16:39:17Z","snapshot_observed_at":"2026-08-06T20:18:52.758625Z","submitted_at":"2025-07-03T16:39:17Z","title":"BERT4Traj: Transformer Based Trajectory Reconstruction for Sparse Mobility Data","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T20:25:36.285685Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2507.03062"},"observation_digest":"sha256:8c55551e41c029474e21609920302cbbe963fbdb30735fdbc14e70ea1795f220","observation_id":"90a85501-8466-469a-aa37-78d6c1f6ce0f","resolution":{"observed_at":"2026-08-06T20:25:36.285685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-06T18:07:19.031418Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.09137","last_updated":"2025-07-12T04:37:52Z","snapshot_observed_at":"2026-08-06T18:00:54.386671Z","submitted_at":"2025-07-12T04:37:52Z","title":"POIFormer: A Transformer-Based Framework for Accurate and Scalable Point-of-Interest Attribution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:07:19.031418Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2507.09137"},"observation_digest":"sha256:30ae8002129159a959f1d0b4fe603813efa8fa174951f509d1f1c6bc0be94693","observation_id":"d411f8c9-ed3e-42ac-86a0-1f8eb6b36649","resolution":{"observed_at":"2026-08-06T18:07:19.031418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-05T23:04:06.902734Z","title":"Multi-scale representation learning for spatial feature distributions using grid cells","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.06584","last_updated":"2025-08-08T03:37:11Z","snapshot_observed_at":"2026-08-06T14:29:19.163640Z","submitted_at":"2025-08-08T03:37:11Z","title":"Omni Geometry Representation Learning vs Large Language Models for Geospatial Entity Resolution","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-05T23:04:06.902734Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2508.06584"},"observation_digest":"sha256:5ace6aff3c88d8a9229191c60e74576bf0c018dec7af61a461d492bc90905348","observation_id":"8887bbdf-de1f-4f94-a11e-2e6a738c84be","resolution":{"observed_at":"2026-08-05T23:04:06.902734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-08-05T19:53:34.548273Z","title":"Multi- scale representation learning for spatial feature distributions using grid cells","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2508.11739","last_updated":"2025-08-15T17:09:48Z","snapshot_observed_at":"2026-08-06T12:22:07.672000Z","submitted_at":"2025-08-15T17:09:48Z","title":"Scalable Geospatial Data Generation Using AlphaEarth Foundations Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T19:53:34.548273Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2508.11739"},"observation_digest":"sha256:731b72f9c29e51447508ead075698acdfba499c9f13b5482ae0ec70a7c567f4e","observation_id":"dec8216c-e296-42c6-b5f5-b9796cfa2b48","resolution":{"observed_at":"2026-08-05T19:53:34.548273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":"2003.00824","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-07-10T10:17:01.611458Z","title":"Multi-scale representation learning for spatial feature distributions using grid cells","venue":"cs.CV","work_id":"bdf5e9f6-17c8-4e85-834f-b0702c579409","year":2020},"citing_paper":{"arxiv_id":"2605.20134","last_updated":"2026-05-19T17:18:32Z","snapshot_observed_at":"2026-07-06T23:30:44.092395Z","submitted_at":"2026-05-19T17:18:32Z","title":"TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-20T06:36:20.078866Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2605.20134"},"observation_digest":"sha256:497ef4aa030cefb5ab3f515f4469eba7c4458e9b36af8a563e85edd7b58f37aa","observation_id":"fc412a95-e4a1-4797-9d34-b7495968f757","resolution":{"observed_at":"2026-05-20T06:38:05.733605Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells","version":1},"cited_work":{"arxiv_id":"2003.00824","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.00824","snapshot_observed_at":"2026-07-10T10:17:01.611458Z","title":"Multi-scale representation learning for spatial feature distributions using grid cells","venue":"cs.CV","work_id":"bdf5e9f6-17c8-4e85-834f-b0702c579409","year":2020},"citing_paper":{"arxiv_id":"2607.08281","last_updated":"2026-07-09T09:22:38Z","snapshot_observed_at":"2026-08-08T04:43:35.584812Z","submitted_at":"2026-07-09T09:22:38Z","title":"Enhancing the KidSat Model: Integrating Geographical Encoding and Data Quality Assessment for Childhood Poverty Prediction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-10T10:08:11.662141Z"},"links":{"cited_paper":"/paper/2003.00824","citing_paper":"/paper/2607.08281"},"observation_digest":"sha256:78fd92c338901dad4d6cab4e1fd53790d92a1bd830ead007c6e77114da7f0270","observation_id":"965afbe4-16bf-457a-a429-c4b641235dc9","resolution":{"observed_at":"2026-07-10T10:17:01.612823Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2003.00824/citation-record","integrity":"/paper/2003.00824/integrity","json":"/paper/2003.00824/citation-record.json","paper":"/paper/2003.00824"},"outbound":[],"paper":{"arxiv_id":"2003.00824","last_updated":"2020-02-16T04:22:18Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T22:16:08.779298Z","submitted_at":"2020-02-16T04:22:18Z","title":"Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2003.00824."}