{"as_of":"2026-08-05T04:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a015a157b41d0b2a1fc4852816baa5540a39e160b7dcb81783bacd18ba1dca50","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T06:16:25.660167Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T15:51:53.040466Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.23533","snapshot_observed_at":"2026-07-14T15:51:53.040466Z","title":"PILOT: One physics-integrated generation framework to unify 2d and 3d radio map construction,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09778","last_updated":"2026-07-08T09:27:28Z","snapshot_observed_at":"2026-07-16T23:18:01.292360Z","submitted_at":"2026-07-08T09:27:28Z","title":"BDFlow-3DRM: Height-Coherent 3D Radio Map Construction via Bi-Dynamical Flow Matching","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-14T15:51:53.040466Z"},"links":{"cited_paper":"/paper/2604.23533","citing_paper":"/paper/2607.09778"},"observation_digest":"sha256:885c5a8870a04e6227f975086b4e349a0c5fdeac94371322797927288e97020f","observation_id":"2e514a46-408c-42e3-b459-6de0212006fe","resolution":{"observed_at":"2026-07-14T15:51:53.040466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2604.23533/citation-record","integrity":"/paper/2604.23533/integrity","json":"/paper/2604.23533/citation-record.json","paper":"/paper/2604.23533"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine learning based clustering and modeling for 6g uav-to-ground communication channels","venue":null,"work_id":"e40cba88-4a33-4e66-9dec-c3c3610be9c5","year":2024},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:7692c75d3378ae70c1826e510da38b70fc865b3abf04eca67dc6026c0746e374","observation_id":"ffd8da0c-141b-4d58-b7a8-7a5ad5595d76","resolution":{"observed_at":"2026-05-26T19:07:53.217228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fast 3-d radio map reconstruction via cross tensor approximation","venue":null,"work_id":"b5e56a29-49c8-4a80-9fea-7c720085959b","year":2024},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:c20759a7f544c8aa681144ef3e50d4d5d89282ccbe623b5d28d5dd29e8a733b3","observation_id":"01e1cd67-05cb-4ec5-b73f-63e12d1095e4","resolution":{"observed_at":"2026-05-26T19:07:53.227001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Digital twin channel for 6g: Concepts, architectures and potential applications","venue":null,"work_id":"adad9992-7f34-4c42-9374-52e418811272","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:f0a92461054dd9fcc594edc69600ca6b66f348807660a13219999edfb8e11c05","observation_id":"ee33e638-038a-42db-a76a-9a4849d43a08","resolution":{"observed_at":"2026-05-26T19:07:53.230495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A scalable and generalizable pathloss map prediction","venue":null,"work_id":"01245958-3a8f-4b45-8e79-bbded4757449","year":2024},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:6fc30fef1bdabffeace0eb26cb022f2882162be7cf5f625e5902fd977899d6ff","observation_id":"410c079d-4809-499e-bff3-b3eabe7aaba3","resolution":{"observed_at":"2026-05-26T19:07:53.233997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ckmimagenet: A dataset for ai-based channel knowledge map toward environment-aware communi- cation and sensing","venue":null,"work_id":"0b9d1679-0221-4c7c-9ffe-b3d2ad687f90","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:54b973b8f4676f98b36472d7a817438b5c777be76d78df314c5773a797bfc27c","observation_id":"98238834-5740-435f-8025-989602a67933","resolution":{"observed_at":"2026-05-26T19:07:53.196987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Radiounet: Fast radio map estimation with convolutional neural networks","venue":null,"work_id":"7f924c31-2be9-46d4-b846-388c3d21b6eb","year":2021},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:ebc8868de6602a0e08d9212b943d3d5e715fa2bed58ff8e4c7abde06996a54a0","observation_id":"221aab8d-71b3-4947-b342-a71e8604eea6","resolution":{"observed_at":"2026-05-26T19:07:53.200578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ra- diomamba: Breaking the accuracy-efficiency trade-off in radio map construction via a hybrid mamba-unet","venue":null,"work_id":"fc7a297f-341b-4e5f-be7a-ca07b673a03c","year":2026},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:b89300646dc814f864d1a199794b2bc98e67cbc4062903ab2ee77670d6d40607","observation_id":"94e4049c-ab6d-4c51-b8e7-d486e1e467d4","resolution":{"observed_at":"2026-05-26T19:07:53.223629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rme-gan: A learning framework for radio map estimation based on conditional generative adversarial network","venue":null,"work_id":"c84786b4-6ff9-4d1f-8294-814541c4a006","year":2023},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:8dd73525fce25b2b4b370cc9aa7d0e4b3f573dceb6e8410409d873fedcdd42cc","observation_id":"7f59049e-577e-4653-97ed-7fcc949078d0","resolution":{"observed_at":"2026-05-26T19:07:53.186201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep completion autoencoders for ra- dio map estimation","venue":null,"work_id":"a2265e25-cf3a-46b8-a8bc-2b205f650c39","year":2022},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:e3bfd5cec1702143fff7ba59a1ad869ca3df546483531e17efc2aa17c6a1f36d","observation_id":"dfc197a4-3ff7-45b6-8a0c-f32b11e5c50f","resolution":{"observed_at":"2026-05-26T19:07:53.236882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.02423","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T17:08:43.165399Z","title":"Llm4pg: Adapting large language model for pathloss map generation via synesthesia of machines","venue":null,"work_id":"682ddb48-512e-4d04-96ec-a97bd1fefac7","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:95afb6a81e2baf8361d5a5cfcc19bca1fb98c41f1569bb958613b205127f2bf0","observation_id":"8b2ed69b-d9f5-45d6-bff7-c91de86568d9","resolution":{"observed_at":"2026-05-11T21:16:12.420475Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context radio map estimation via ripple autore- gressive modeling","venue":null,"work_id":"5695cc20-6004-4f52-a11b-5ab652d96baf","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:7e7f3074989c31658d6cba3f27e026ed094cd5944a1eb63886ee81e44757a082","observation_id":"3a50f97d-01ac-432d-ba33-da2f5df8f101","resolution":{"observed_at":"2026-05-26T19:07:53.220344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Radiodiff-3d: A 3d× 3d radio map dataset and generative diffusion based benchmark for 6g environment-aware communication","venue":null,"work_id":"746b5d45-1938-4e81-89a7-3a25c48f15d7","year":2026},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:807d46f3a4d65facf9c1e3e0c062786c2b1d9ca00c3272ea9a2d25377fc51b0b","observation_id":"82f3b0f5-82b3-48b5-8e21-df22c82bab71","resolution":{"observed_at":"2026-05-26T19:07:53.206882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/tccn.2024.3504489","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction","venue":"IEEE Transactions on Cognitive Communications and Networking","work_id":"cbc183ba-9239-48c0-ad9c-7b56c09bf826","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:05d8ab206eee7eb5513762d7146b18a3092a723b2a3dadad4a969609f39b8117","observation_id":"01a58f2d-0e1c-413a-9dac-ba3bbb0a6bc8","resolution":{"observed_at":"2026-05-26T19:07:53.193702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Randar: Decoder-only autoregressive visual generation in random orders","venue":null,"work_id":"315abaa0-cf62-4cc0-918c-293a52ea7afe","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:4ce3725243dc517c1dbf4d390e5df0edee1cb1feefe7b4a35665eba567353b7f","observation_id":"f88c8656-cd7e-475e-b984-5d8038f4e9ac","resolution":{"observed_at":"2026-05-26T19:07:53.239413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06525","last_updated":"2024-06-10T17:59:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-10T17:59:52Z","title":"Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation","version":1},"cited_work":{"arxiv_id":"2406.06525","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.06525","snapshot_observed_at":"2026-07-10T11:37:03.266757Z","title":"Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation","venue":"cs.CV","work_id":"41efe203-9377-4c63-b1d6-e499cd6e46f6","year":2024},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"cited_paper":"/paper/2406.06525","citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:361cbc4c057e84f6e5c628456ba20063879f3d84ec0a6409278bc0150b136a8a","observation_id":"daa64acb-7503-4737-b5a1-56b431dfcb9a","resolution":{"observed_at":"2026-05-11T22:09:17.130563Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":"05940bdf-6254-48d7-a805-3eaf2dcb3d24","year":2022},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:a074576056360983abe5fd1af871292123cf1b270232d319c1724d8e85eb4a01","observation_id":"7aa726f2-f50e-4a40-ac33-fe82addb62bc","resolution":{"observed_at":"2026-05-26T19:07:53.213945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diveq: Differentiable vector quantization using the reparameterization trick","venue":null,"work_id":"3527ec7c-f7c9-4cad-a82b-e58e31f462bc","year":2026},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:c635ce0db8c9b796bfd43bac54654315db6d3bdccd5bbbe1bdc636f54bc1e195","observation_id":"1ce99cac-6a1d-4bf8-b4b7-cf4c0fe9a630","resolution":{"observed_at":"2026-05-26T19:07:53.189475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep multi-scale video prediction beyond mean square error","venue":null,"work_id":"c966f6ec-d171-41af-bfe3-e10eec6cc37e","year":2016},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:1766bcb74746dc92d8ac287ee05309008682d39667ee7009b988c60183109f0c","observation_id":"e1a06a59-f60c-4d17-aaf8-f8904911165a","resolution":{"observed_at":"2026-05-26T19:07:53.211420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Addressing representation collapse in vector quantized models with one linear layer","venue":null,"work_id":"2c6c5d11-1c3e-42ca-bd8c-c85fa368a383","year":2025},"citing_paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T06:16:25.660167Z"},"links":{"citing_paper":"/paper/2604.23533"},"observation_digest":"sha256:d3164351b2fc9f6c3960efa420f45882c2f38b6ce4fa1d43c1fe8a091515488c","observation_id":"2c605c5a-c0f3-441b-b66d-ece0fd4eac5c","resolution":{"observed_at":"2026-05-26T19:07:53.203826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.23533","last_updated":"2026-04-26T04:57:01Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-07-31T15:53:04.039780Z","submitted_at":"2026-04-26T04:57:01Z","title":"PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":17},"total_outbound_references":19},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2604.23533."}