{"as_of":"2026-08-08T21:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:71fb9d17ecbaade61aa1802e6bfb57897a8d376c84fdb66c96bea8db0df424d5","coverage":[{"denominator":71,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":71,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T14:09:30.395518Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.10120/citation-record","integrity":"/paper/2607.10120/integrity","json":"/paper/2607.10120/citation-record.json","paper":"/paper/2607.10120"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"2025.Claude 3.7 Sonnet and Claude Code","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:509c922c69af424af9f8345f3abe48cf478175a72b045686ad129bbb14c819d7","observation_id":"59f7e08c-a79c-415c-ba7f-777085d2c32c","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-07-06T22:37:03.716474Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:49579570170ae456df9ec942d877d4233419f7f0ff0be6fe3555b1240bbe7c84","observation_id":"2dbd7b9d-471a-4cdf-8a6e-f140143e83ee","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:ee1218b6a75f885c55226a4cf034e9c09815eb3032fcb946ed442cb6bc2c3718","observation_id":"2db374fd-cfbf-484b-9b61-456e6e004349","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:881245ee42bc70789b438fe2d7d4e02f5e31edadf877da24441b15f30b1e7fe5","observation_id":"ab9122a9-089d-4109-9ffb-cdc75f0f4c6c","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.11310","last_updated":"2026-04-10T18:50:16Z","snapshot_observed_at":"2026-07-06T22:41:58.373427Z","submitted_at":"2026-01-16T14:06:46Z","title":"Context-Aware Semantic Segmentation via Stage-Wise Attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.11310","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2601.11310","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:09339940f70e02d2af1079631fc352b795b5b41a17bf9040f9d2a7e46debfdd9","observation_id":"f82a103b-b458-4e63-a1a2-a89b7b3e7a1d","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07847","last_updated":"2025-06-09T15:09:49Z","snapshot_observed_at":"2026-08-07T05:21:44.165656Z","submitted_at":"2025-06-09T15:09:49Z","title":"F2Net: A Frequency-Fused Network for Ultra-High Resolution Remote Sensing Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07847","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2506.07847","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:0543ee1bbbbe270f035fcb2a96f535f5b2f77fd027a9e834fccd3b7d4da73193","observation_id":"28cd82e5-b6df-4e03-a3c9-37727bbf2c83","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:52781eb6a33939b45eb98008b1745f263de16985d046d265a45841c28de69a9d","observation_id":"baa33ae6-0bda-4423-bb4e-fb1604578df6","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:8763c15d4429e80dea5b4653db93956a3edc50cde2beec2083a694c86f7b59b4","observation_id":"78c7a61b-1e9f-468c-83b1-a7e44d5577ac","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e51348692f3794d1d0bd99d662da336377c459b503e3a51384881e23529cf089","observation_id":"f902a8eb-3382-4266-90bb-cf20d3ea30a3","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.16500","last_updated":"2024-08-29T12:59:12Z","snapshot_observed_at":"2026-08-05T11:54:14.447608Z","submitted_at":"2024-08-29T12:59:12Z","title":"CogVLM2: Visual Language Models for Image and Video Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.16500","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2408.16500","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:4172b75a587786ced6397cf6f6728df91ac19011ca882b91190a1abe9d00036e","observation_id":"0e3f8377-2e3d-4766-97cc-b1d086c7d0c0","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.15266","last_updated":"2023-07-28T02:23:35Z","snapshot_observed_at":"2026-08-05T09:46:05.780158Z","submitted_at":"2023-07-28T02:23:35Z","title":"RSGPT: A Remote Sensing Vision Language Model and Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15266","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2307.15266","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:7d0f0a6cc2787e42ef4f0964effe86d135c2ec918662663e44e9d557ebcdda56","observation_id":"702be6a7-ebeb-4edb-9787-cc5e61a184f9","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:9c1cc0adb8d088b9801c737e964491059b18d486f998521c978d67a41fcd2bb8","observation_id":"ab7de4ba-0fa6-4cbf-b471-76149cb1f6f4","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"InProceedings of the 32nd ACM International Conference on Multimedia (ACM MM)","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:f5f7eb495b69dbd65917a022e18cb8a82ae2957f603df3d07ee4995d73be1b1d","observation_id":"4c099494-ee6c-482a-8074-2c5c63adda2e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:505df34a431c68a93f81f128aae16d4cdeb93e918254b4c19fe52b2b6b173247","observation_id":"f4875e30-b956-4d62-b8f6-36cd3f18541e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:c9208756249f525d1f0dbeb6d6a057fe7223f30eb133126615172d8966825067","observation_id":"5fd23513-e502-4364-a8b9-593c8ee2ba93","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:c4722eff7bd47fcf1fbb4dd80bafc74d0654768aa42ae3b74cb9de1c94eb9bb0","observation_id":"9e243c1e-ff3c-48f3-86ac-7fa37877778e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03326","last_updated":"2024-10-26T16:35:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:59:44Z","title":"LLaVA-OneVision: Easy Visual Task Transfer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03326","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2408.03326","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:3ba062c04ccabd4eb4694dc63ef3bd60a3d6538b1cfdf3dc415c324568ba4d96","observation_id":"8d598f3e-4b6b-456a-b9bb-bd6194417fa6","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:b29304a5055c242250af60560faeea6c30b551ba1653894ddecb26c6f6d2d670","observation_id":"a3a566f8-cc48-4e41-be88-c02549555662","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:9588944bc97bdc2a3eb533b1560a15c8f4a5f7c4c7f8de283d6bb0430e9d2d32","observation_id":"16caf778-6078-4d9a-a51c-b056a807c90c","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:832a50391214dff8d8ed0a0feb19f681278151b1fb0e563f8a010a9a34473553","observation_id":"59f39403-f086-4a27-b99c-676f2b078591","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:482923698ce179e802c0794dcb3ab2639d8b770e3f3f0fcecc0c9171518f3c53","observation_id":"1d6840f0-2d77-4bce-b06c-937094505431","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:36c147df30cf0da68927b0348079d0212839fc68a81bbb6ba3662f94c3e7135f","observation_id":"e101a9c9-0463-48d0-a262-035a35379d7f","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e8ddbeb35949de14561edcfa8c92861797549bd44f02d3443c339ea3345a9b3e","observation_id":"9c76a625-9090-4429-8f69-0fda029c224e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:aeb9f59b9f6e3e5023d5b59bd7f5151985d8262f927794393316bab4a87b2ad1","observation_id":"6c8642e1-db14-45ad-9ad8-3ace042973cd","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"2024.LLaV A-NeXT: Improved reasoning, OCR, and world knowledge","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:267c7be93819638186f4f2e5f503edb30effb603a8b0c98b4301db1599752e92","observation_id":"9c934673-2ea7-4372-ac39-4d436e22df83","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:0a15760f414526f4cefce7f5102a05a19b48be83a943396dd1bf573b6dd68df2","observation_id":"dfb6c88d-bbfc-4165-84b3-25129a9c305e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:ebfe19eecbcd98a798b9010be5c56d337cc7c7a0fb99dc010c4b00ca787b0f5e","observation_id":"5b065fbf-6860-4db2-b407-deb01e2dfc3f","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:d6173a655d0da1d2f037ff297f603155d5de018e03c0ad041efd7b084e2a600f","observation_id":"5e9ec869-27bf-4463-a5ee-ca6a3b945ca5","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:9eeee5d54744f469851b8d53aa31c361df0c2fb031ba5768657b9bf5bc998d85","observation_id":"1c6db654-e5dc-4d0f-a055-29731d6f73a8","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:52f7f165281a941d84783e3ee72eab56c15e9cc7a3b267186b50fbc1aec61870","observation_id":"48b773db-7e52-467a-b879-324ba8eae6cd","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05679","last_updated":"2024-12-10T02:23:30Z","snapshot_observed_at":"2026-07-06T20:03:16.082369Z","submitted_at":"2024-12-07T15:11:21Z","title":"RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05679","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2412.05679","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:98f17a811a90a9bba010cd4824681df5605d7c2d5466a6ff82ced2cc0f673918","observation_id":"a4009fd8-4c32-408a-933c-a8c1654a3083","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:164ae8b0877b98097954884928838c97792520df719b152d5aa5bd746d308f6d","observation_id":"4407ad47-b71b-44a4-875d-e39183c6e8a0","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.07588","last_updated":"2025-07-24T07:44:45Z","snapshot_observed_at":"2026-08-07T17:15:57.968218Z","submitted_at":"2025-03-10T17:51:16Z","title":"When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.07588","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2503.07588","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:f9a13f11dc1baec8381a500b6b8a62fb4cf8c708c20ea8e8b79d533330001a63","observation_id":"4c4dfee1-47cf-4cfc-aeda-075996c8f3bb","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e205d548e1eb9edacde8043fa1b91f14d840bbdef011731589b1ff5966e30ff5","observation_id":"b3981780-c0ea-48ce-9323-558a579a16ad","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:b0e772e0f5919efa36583e7036b56284589ae6e9f199921d772538535e7c1d39","observation_id":"c85a6a29-f921-4aaf-bef9-fc50ba0a2467","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"2024.GPT-4o mini: advancing cost-efficient intelligence","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:de68a2e94763d1d00a96004695cac44044197eced4a6c2741cb457dad59f0eea","observation_id":"c062d659-1be7-41e7-8640-c7debeea0188","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"2024.Hello GPT -4o","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:2bc6e84925661e0f250c4359f10dfb0e04a25ef16da08305f83cce9fe1e6bd45","observation_id":"1385d3d2-b6c0-4dc3-8c74-727007053558","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.06828","last_updated":"2025-03-13T08:16:01Z","snapshot_observed_at":"2026-08-02T08:53:20.872349Z","submitted_at":"2025-01-12T14:45:27Z","title":"GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.06828","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2501.06828","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e468eb21b5d7d8a42fe071b63de1947c6945837dfeb96ac54e8d95e9da8cce72","observation_id":"1b903af9-48f8-45b4-8a74-25804925781b","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:2fdb6be3ae892a785bdb1a04e944b87db99ee4c7c499ed746160b76f15865d69","observation_id":"40e24159-cd35-419a-976e-e969d42ca3cf","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:72a09cbab88bf418cf339dd5778ca4fcddc1e85acdc3be8b1f3f36651e955246","observation_id":"d441a222-1911-4267-af1a-7c0a139a82c4","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.13925","last_updated":"2025-01-23T18:59:30Z","snapshot_observed_at":"2026-07-31T01:05:18.406030Z","submitted_at":"2025-01-23T18:59:30Z","title":"GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13925","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":"Khan, and Salman Khan","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2501.13925","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:79dcf3445ed9b8d35eee5a471ea5b2963b833a707cbd28eb6a377e6bad527bdf","observation_id":"3d82469c-2594-4623-9476-ad8c23d7a288","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e09f942c730f7d6b88b9ef3f637dc20690af2085e8586cfb1d6d235bb8c0915f","observation_id":"9baa0608-8ea7-4cf3-8033-cc8bff7e4f3d","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.22396","last_updated":"2026-04-08T01:53:03Z","snapshot_observed_at":"2026-07-06T22:37:08.086095Z","submitted_at":"2025-11-27T12:19:37Z","title":"Asking like Socrates: Socrates helps VLMs understand remote sensing images","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.22396","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2511.22396","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e3dd5d8801784203d1cd241c44592afd924f1759abed7b834f40217743ee4ef4","observation_id":"8632ae4a-e47f-4dc1-b93c-70b999c8902b","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.16044","last_updated":"2025-09-01T02:39:51Z","snapshot_observed_at":"2026-07-06T19:56:17.117739Z","submitted_at":"2024-11-25T02:15:30Z","title":"ZoomEye: Enhancing Multimodal LLMs with Human-Like Zooming Capabilities through Tree-Based Image Exploration","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.16044","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2411.16044","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:7772cd5935c46a1c8c66118ee152bb0d5aae282c5d3566c8cd22e9f06d22493c","observation_id":"e912b465-8b2e-418b-a622-9c4be1ac5a3d","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.06475","last_updated":"2024-02-09T15:31:01Z","snapshot_observed_at":"2026-07-06T17:28:02.037844Z","submitted_at":"2024-02-09T15:31:01Z","title":"Large Language Models for Captioning and Retrieving Remote Sensing Images","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06475","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2402.06475","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:5a03d06de88006bf805772f4c6fe4f588e29eb6f4e55b019c1d887354b13ddf3","observation_id":"9055eae1-c298-4208-b2ac-8dd227ea2830","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:ca350a912680830e392b6d1c3738dcb130c7781962f6c0156f038e080d68e011","observation_id":"2312c5a7-c591-4092-a85b-73e16d762018","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:874bab50a57f15756d9354b703daa231eaf878ec3dc414ef1332e26e74d04acd","observation_id":"a604fac5-b479-45e4-98fa-17c5502ffb23","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:1780976b6f13a73501603e5feb41f372e55eb66258a37955f299e7d8f2925f72","observation_id":"02de2905-825b-4177-8cbf-a22ba0470ae1","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:d97a85495b0754aceff90b7ceb0486882e07b9d3f3310836579004acc41611e2","observation_id":"e3793497-f7dc-4971-a5df-8d656696534b","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:0eb6b9a1308b8cb33e9bfa99703e9136f3b25960c3d5b1c985b7111fcee81bb5","observation_id":"73567441-f554-45e1-96f8-2c8e1cb05e71","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:2387291c21bbbf2699fddfc1b866d96fa8c8b37dd7be59934eadd542cf3a5986","observation_id":"7d85db21-4a09-49f9-b675-bb0ecdf9cac6","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:a7518688e1631b969ce3b6db73126ac87d803ce77841d6683840d2d2852a56bf","observation_id":"336dfaf6-bef7-49b8-91b7-f0291d0663a4","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:9e53dfd04b31ea934415c2ec353677ac82a9adf462b56448377b82d9327a731f","observation_id":"b3c5b54d-d985-4cbf-a6c3-52dff3314fe1","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:0e6af1b74c10995fe2c83077695a3d500a20ef6ecf57a2c4edd04b9fc3d7a7e0","observation_id":"ffc7ba69-e343-4229-b620-4d6fd5e4b629","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.04451","last_updated":"2026-05-06T03:25:41Z","snapshot_observed_at":"2026-08-03T00:29:16.867900Z","submitted_at":"2026-05-06T03:25:41Z","title":"RemoteZero: Geospatial Reasoning with Zero Human Annotations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.04451","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2605.04451","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:7631683a5da10ffc9701039ad8a00e956582675481b659662c6477e88c92b7a6","observation_id":"257aab3f-e3d8-43a8-b14f-e74b6d2a7110","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.07765","last_updated":"2026-04-12T05:49:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-09T03:40:46Z","title":"RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.07765","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2604.07765","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:81b271ac44416cb87f398ff91fe88f473fd4b04a77bd854c0987b17735ac6ee2","observation_id":"f005c587-d693-436b-9849-285692d85aa1","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:7236de68867f60396099ee046bdeb2fd19c3de4cba2ef6f7122a48e5969fe515","observation_id":"4ff6cba4-5e67-444e-9ea6-e64e91a8791e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e8c148d16f47dc884016dae8e564a8099af7bbd9bf21391a4924b6928f0d7ce3","observation_id":"e7050ac9-a06f-4ea1-bf7b-ebff9e127514","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.03320","last_updated":"2024-07-03T17:59:21Z","snapshot_observed_at":"2026-08-04T22:09:42.241578Z","submitted_at":"2024-07-03T17:59:21Z","title":"InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.03320","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2407.03320","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:fc834a919fdd60ef9bd21ff7701601c00994b4e83fabf346833a1193711ab690","observation_id":"8e167f3e-02fe-4f42-871f-3923a118714e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:19178bd24f33339df252dede3cb1606fd28f16330c38a10b781c1f7afd2a464d","observation_id":"cc0ce847-2512-466d-a411-aa1a5b0909da","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:bd131b5901b1bd6dbac31ce8b5c9ccf178fab2c5b49efeb9b927aaa3a854902f","observation_id":"b4ad68c6-0e4d-4c3b-80fc-30887963948a","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:6f3fdb610dbdf2d86786ebdb71c3a343dabc71c275bee19d6e8c004bb559fa70","observation_id":"e74b4dd7-d35c-4a52-9a27-46348664a88d","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2512.19302","last_updated":"2026-04-21T02:16:23Z","snapshot_observed_at":"2026-07-06T22:39:48.048525Z","submitted_at":"2025-12-22T11:46:42Z","title":"Bridging Semantics and Geometry: A Decoupled LVLM-SAM Framework for Reasoning Segmentation in Optical Remote Sensing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2512.19302","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2512.19302","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:9b368f4b83e54fccb3df327ee3d90a4721d6e25a30930f4a73bd3acd37b36019","observation_id":"ebcbd825-0e8b-4a7e-b1ec-ee21ced0ed41","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.13257","last_updated":"2025-02-05T08:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-23T17:59:51Z","title":"MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.13257","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2408.13257","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:48c34d0781fe5a76550de934d184e35e51c64f541b9582a4e81133cad28e6079","observation_id":"289129be-1ae5-4590-8b6c-4bcd44eca537","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.21976","last_updated":"2026-04-23T16:06:02Z","snapshot_observed_at":"2026-08-05T07:42:29.124541Z","submitted_at":"2025-09-26T07:01:12Z","title":"Geo-R1: Improving Few-Shot Geospatial Referring Expression Understanding with Reinforcement Fine-Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.21976","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2509.21976","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:3e82606e2255e0c1c67e078a86125d353b34e60d7a0c6a8309d9bee62d6012e4","observation_id":"f62214d7-32a7-42d4-9cc1-10cec4990bfa","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:a3d56fa551735b4a046aa51d2219f3fdc28c48479a0264dab984eedb41de5795","observation_id":"5440a71b-9aaf-42ed-8a93-47bdca596967","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:594362dfe865ec75c9790bca999d12e545178c16e71f2146c1746108cc3f30fa","observation_id":"47e2fb85-77a2-48d0-8958-dff8f30fbff6","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:bd7530a681227266a9ce8dd96b1c493c48eb7b48219f797c2616843586cf9074","observation_id":"cf57de2b-3eb9-45a3-b19f-f89e0dffdf3f","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:e024e995c80a76516e30f3c50253f8bc878baf850d112c94dd99091c150a6384","observation_id":"56b6163b-73cb-4fa8-bca7-08ad93fd5616","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:76f98badc689acad09fd16ab2fba9184adf571fb9df1601b451a0b175949e449","observation_id":"bf695797-2c95-46ed-b52d-f489ea90b09e","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10479","last_updated":"2025-04-19T03:47:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-14T17:59:25Z","title":"InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10479","snapshot_observed_at":"2026-07-14T14:09:30.395518Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-07-14T14:09:30.395518Z"},"links":{"cited_paper":"/paper/2504.10479","citing_paper":"/paper/2607.10120"},"observation_digest":"sha256:a2c9193aa03b7186f978badd1c0e1781c4f95643e030083c773bd5b861ddd8db","observation_id":"ebca0a8b-9c4f-46d3-952e-96939de8b3de","resolution":{"observed_at":"2026-07-14T14:09:30.395518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.10120","last_updated":"2026-07-11T04:56:27Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-03T00:19:08.090846Z","submitted_at":"2026-07-11T04:56:27Z","title":"WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding"},"reference_resolution":{"displayed":71,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":71,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":71},"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 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2607.10120."}