{"as_of":"2026-08-07T21:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3af85a67b2967d6db7bd6b6513f2575c7ca715b10ef337d9704f8e01452f6bd2","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:47:12.923658Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-19T09:32:15.971097Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-08-07T14:47:12.923658Z","title":"Citygpt: Empowering urban spatial cognition of large language models.arXiv preprint arXiv:2406.13948, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.17572","last_updated":"2025-05-23T07:30:57Z","snapshot_observed_at":"2026-08-07T14:42:21.962648Z","submitted_at":"2025-05-23T07:30:57Z","title":"USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:47:12.923658Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2505.17572"},"observation_digest":"sha256:d5b87684b71d6da68a6de2329b92e1b8d34ac96163f99c57f438c9816e66a801","observation_id":"90ac15c2-34fb-41be-9f7e-e7ba2f5f5eb2","resolution":{"observed_at":"2026-08-07T14:47:12.923658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-08-07T13:52:56.982140Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20874","last_updated":"2025-05-27T08:22:58Z","snapshot_observed_at":"2026-08-07T13:43:13.230007Z","submitted_at":"2025-05-27T08:22:58Z","title":"Can LLMs Learn to Map the World from Local Descriptions?","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T13:52:56.982140Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2505.20874"},"observation_digest":"sha256:0bb5c0b3db22a025aee567299b4525bab3c1f2313a05dc06201d4fee320adb2c","observation_id":"e9076cc4-4451-4e07-8300-c6317c582b72","resolution":{"observed_at":"2026-08-07T13:52:56.982140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":"2406.13948","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Feng, Yuwei Du, Tianhui Liu, Siqi Guo, Yuming Lin, and Yong Li","venue":null,"work_id":"a706ea95-bb19-4da1-8a25-3bd3227ec799","year":2024},"citing_paper":{"arxiv_id":"2506.11512","last_updated":"2026-05-08T13:38:42Z","snapshot_observed_at":"2026-07-06T21:41:33.629441Z","submitted_at":"2025-06-13T07:13:05Z","title":"From Time Series Analysis to Question Answering: A Survey in the LLM Era","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-19T09:31:55.829045Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2506.11512"},"observation_digest":"sha256:2a6bcb71f44c8f92d827b9c3dee8c37c9038c534a6b462d09f90a37e9a3ba4e2","observation_id":"03cfce81-0071-4574-809e-af0d5988bd7e","resolution":{"observed_at":"2026-05-19T09:32:15.974554Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-08-06T21:07:06.340205Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.00914","last_updated":"2025-07-01T16:18:29Z","snapshot_observed_at":"2026-08-06T21:00:13.313278Z","submitted_at":"2025-07-01T16:18:29Z","title":"Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T21:07:06.340205Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2507.00914"},"observation_digest":"sha256:0b44833549fc83fb0a77326867f2fdb23d1958d77d7a8685c93ef281b8bd8bd1","observation_id":"9c6de3b8-5a34-440a-96da-d12ba365bd04","resolution":{"observed_at":"2026-08-06T21:07:06.340205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-08-06T14:20:37.640195Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19586","last_updated":"2025-07-25T18:00:21Z","snapshot_observed_at":"2026-08-07T07:05:05.653675Z","submitted_at":"2025-07-25T18:00:21Z","title":"Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T14:20:37.640195Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2507.19586"},"observation_digest":"sha256:7182f172a853f8c4c93b190646279b1c4b51ef3167eb1e70475a4db8f7cb40e9","observation_id":"b9864230-f6c5-4a8f-aab5-199e1b666f02","resolution":{"observed_at":"2026-08-06T14:20:37.640195Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":"2406.13948","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Feng, Yuwei Du, Tianhui Liu, Siqi Guo, Yuming Lin, and Yong Li","venue":null,"work_id":"a706ea95-bb19-4da1-8a25-3bd3227ec799","year":2024},"citing_paper":{"arxiv_id":"2604.08033","last_updated":"2026-04-09T09:38:15Z","snapshot_observed_at":"2026-07-06T22:57:13.745326Z","submitted_at":"2026-04-09T09:38:15Z","title":"IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T17:49:16.409834Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2604.08033"},"observation_digest":"sha256:2372653ad2fa6c4aedc2b154c14253153b773778066852c768cd70a1d9ad92d0","observation_id":"c15d24d4-3224-4f9b-b0d4-11ff57390a71","resolution":{"observed_at":"2026-05-11T06:05:56.865835Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13948","snapshot_observed_at":"2026-08-04T21:44:53.717220Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01753","last_updated":"2026-08-03T06:21:05Z","snapshot_observed_at":"2026-08-07T09:22:29.683777Z","submitted_at":"2026-08-03T06:21:05Z","title":"Can Urban Blight Be Accessed with Vision-language Models: A Case Study in Detroit","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T21:44:53.717220Z"},"links":{"cited_paper":"/paper/2406.13948","citing_paper":"/paper/2608.01753"},"observation_digest":"sha256:b50f95af7d025a7592c0c6dfac72d7e0e3d9d4c4dcbcd746504b97b6f97b0014","observation_id":"dc353b8b-db2a-46f1-a6fd-752466a04fff","resolution":{"observed_at":"2026-08-04T21:44:53.717220Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.13948/citation-record","integrity":"/paper/2406.13948/integrity","json":"/paper/2406.13948/citation-record.json","paper":"/paper/2406.13948"},"outbound":[],"paper":{"arxiv_id":"2406.13948","last_updated":"2025-05-31T15:26:01Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-03T10:35:34.153257Z","submitted_at":"2024-06-20T02:32:16Z","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.13948."}