{"as_of":"2026-08-08T12:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6317a78e22321570ff48cebef39bbd22be1d474e56d074727c3f51ebc58dda89","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:29:04.050542Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"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/2608.05793/citation-record","integrity":"/paper/2608.05793/integrity","json":"/paper/2608.05793/citation-record.json","paper":"/paper/2608.05793"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.09996","last_updated":"2024-11-15T07:01:44Z","snapshot_observed_at":"2026-07-06T19:50:46.576709Z","submitted_at":"2024-11-15T07:01:44Z","title":"Building 6G Radio Foundation Models with Transformer Architectures","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.09996","snapshot_observed_at":"2026-08-07T23:29:03.850180Z","title":"Building 6g radio foundation models with transformer architectures,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.850180Z"},"links":{"cited_paper":"/paper/2411.09996","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:ee3f763c6a30a3b17545a1d1bd5858185a55a388e4686014d0ca996f490c5ca3","observation_id":"5bb132ac-fe50-4081-abc5-0a169463cace","resolution":{"observed_at":"2026-08-07T23:29:03.850180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.14100","last_updated":"2025-04-18T22:51:35Z","snapshot_observed_at":"2026-08-07T16:01:00.215644Z","submitted_at":"2025-04-18T22:51:35Z","title":"6G WavesFM: A Foundation Model for Sensing, Communication, and Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.14100","snapshot_observed_at":"2026-08-07T23:29:03.856048Z","title":"6g wavesfm: A foundation model for sensing, communication, and localization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.856048Z"},"links":{"cited_paper":"/paper/2504.14100","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:cad75c2a4a6fc4ce71bf546aa44d5075c1f1908d0fee26832e271e23a3032fb0","observation_id":"14e29186-cff2-437b-8e73-8ef53da4a1fa","resolution":{"observed_at":"2026-08-07T23:29:03.856048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.13637","last_updated":"2026-06-24T08:13:26Z","snapshot_observed_at":"2026-08-07T22:35:50.548609Z","submitted_at":"2025-07-18T03:50:29Z","title":"Towards channel foundation models (CFMs): Motivations, methodologies and opportunities","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.13637","snapshot_observed_at":"2026-08-07T23:29:03.861286Z","title":"Towards channel foundation models (cfms): Motivations, methodologies and opportunities,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.861286Z"},"links":{"cited_paper":"/paper/2507.13637","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:d90133a757fdb8686a8926e1d850334a657b57063f8d8ce62237c6d9866bec19","observation_id":"7acd08f7-09f2-42e0-bce9-5e19a3afe0b7","resolution":{"observed_at":"2026-08-07T23:29:03.861286Z","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":"2026-08-07T23:29:03.866429Z","title":"Wifo: Wireless foundation model for channel prediction,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.866429Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:41c7f5f971509e7bcd61c7233390c5fb73a828357cb25c525e2d827b32b1c28d","observation_id":"ae03e123-7b7a-410c-ae0d-a19afb8b39db","resolution":{"observed_at":"2026-08-07T23:29:03.866429Z","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":"2026-08-07T23:29:03.871662Z","title":"Tiny federated wireless foundation models for resource constrained devices,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.871662Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:47758a2f01490235b208106e272106c104408ac71e58e4e814b17369bea00058","observation_id":"f20868a3-825b-4576-9aaf-205bf9dad3eb","resolution":{"observed_at":"2026-08-07T23:29:03.871662Z","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":"2026-08-07T23:29:03.876837Z","title":"Scale what counts, mask what matters: Evaluating foundation models for zero-shot cross- domain wi-fi sensing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.876837Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:d0b0df3df5807236cabf0346c39870e527d954c62ce71d93a499860ad7f7bdf1","observation_id":"1e0e2d74-a93f-4390-99de-7fe926add973","resolution":{"observed_at":"2026-08-07T23:29:03.876837Z","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":"2026-08-07T23:29:03.882283Z","title":"Multimodal wireless foundation models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.882283Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:24969644418dc30775b9ad2db81064badb6e6a185b7fd4aa7114ce7ebaa02660","observation_id":"6cadefc9-641d-4461-944d-b03adbc55d26","resolution":{"observed_at":"2026-08-07T23:29:03.882283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.10134","last_updated":"2025-05-15T10:04:44Z","snapshot_observed_at":"2026-08-07T15:45:08.074762Z","submitted_at":"2025-05-15T10:04:44Z","title":"Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.10134","snapshot_observed_at":"2026-08-07T23:29:03.886803Z","title":"Large wireless localization model (lwlm): A foundation model for positioning in 6g networks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.886803Z"},"links":{"cited_paper":"/paper/2505.10134","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:3e6b3f4035c5b4364175000a3fba422dc24a7d29c44b1074fe2fc6739c26c099","observation_id":"5b4d32a6-5f1c-44cc-922f-32915368c1ee","resolution":{"observed_at":"2026-08-07T23:29:03.886803Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.990830Z","title":"Rf-diffusion: Radio signal generation via time-frequency diffusion,","venue":null,"work_id":"2283b2cb-6918-4f24-9bba-bedec281d8fa","year":2024},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.891688Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:9d1c5bc9f07ac46f6453e76730750cc4ed615cefc5da1a27f824d840da807abf","observation_id":"81e01274-3ce1-4da3-beb0-3ecacb118948","resolution":{"observed_at":"2026-08-07T23:29:04.995828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06877","last_updated":"2025-02-08T12:38:56Z","snapshot_observed_at":"2026-07-06T20:34:15.946558Z","submitted_at":"2025-02-08T12:38:56Z","title":"WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06877","snapshot_observed_at":"2026-08-07T23:29:03.896033Z","title":"Wirelessgpt: A generative pre-trained multi-task learning framework for wireless communication,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.896033Z"},"links":{"cited_paper":"/paper/2502.06877","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:df63657fbe59db932a32084eeb1221d0435bc8c9f7e24d7599cc45ca85f4c75c","observation_id":"003a417f-ad6f-47d2-ae06-1d26ecdd67e3","resolution":{"observed_at":"2026-08-07T23:29:03.896033Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.00274","last_updated":"2025-08-01T02:49:18Z","snapshot_observed_at":"2026-08-06T10:17:46.455111Z","submitted_at":"2025-08-01T02:49:18Z","title":"RIS-MAE: A Self-Supervised Modulation Classification Method Based on Raw IQ Signals and Masked Autoencoder","version":1},"cited_work":{"arxiv_id":"2508.00274","doi":null,"metadata_source":"pith","pith_arxiv_id":"2508.00274","snapshot_observed_at":"2026-08-07T23:29:04.135556Z","title":"RIS-MAE: A Self-Supervised Modulation Classification Method Based on Raw IQ Signals and Masked Autoencoder","venue":"eess.SP","work_id":"adcdc8f9-9353-4125-bda8-dde7b19107f7","year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.900667Z"},"links":{"cited_paper":"/paper/2508.00274","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:e35a0dedd3b7cdc6e3c22cf5b8c61575d6c975c425153d9d15a7be0a8461753b","observation_id":"4406adf5-8aad-455c-9241-a8f639cac6c2","resolution":{"observed_at":"2026-08-07T23:29:04.143372Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.975354Z","title":"Spectrumfm: A foundation model for intelligent spectrum management,","venue":null,"work_id":"019060d6-1b1c-4560-941a-5b652c04c984","year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.905670Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:05efaa4410b7951b3835ebad8d47d8c20f53eee7165e0404b43687414a90278c","observation_id":"d8e83287-c6c8-4dec-93bf-7ee4b7371a85","resolution":{"observed_at":"2026-08-07T23:29:04.980245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.18785","last_updated":"2025-08-26T08:11:57Z","snapshot_observed_at":"2026-08-05T21:28:50.302480Z","submitted_at":"2025-08-26T08:11:57Z","title":"EMind: A Foundation Model for Multi-task Electromagnetic Signals Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.18785","snapshot_observed_at":"2026-08-07T23:29:03.910400Z","title":"Emind: A foundation model for multi-task elec- tromagnetic signals understanding,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.910400Z"},"links":{"cited_paper":"/paper/2508.18785","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:b17d9b230e98e12b6b9b820951c5d289fcfdaa721a2f0e916a54bebd4edb95da","observation_id":"5da6ccf4-4fd6-469b-8b10-892250bf2269","resolution":{"observed_at":"2026-08-07T23:29:03.910400Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.959394Z","title":"Large- scale real-world radio signal recognition with deep learning,","venue":null,"work_id":"70e0aa77-1cac-45e6-a82b-703cebf3012b","year":2022},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.914868Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:d6f913cde5109bdfdc54a79e515ddad55a90a45b587e6899c8778f491a04ec67","observation_id":"2f2bc4fc-8cb8-4655-9742-68cd7ee8a99c","resolution":{"observed_at":"2026-08-07T23:29:04.964351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.938058Z","title":"Convolutional radio modula- tion recognition networks,","venue":null,"work_id":"31205744-e5d9-49b5-bbb2-1fd1b72414aa","year":2016},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.919707Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:d0a5349db001853391d5b8c206dd6f4f0584d6f6bcff1f0bc5e904eaeb98332e","observation_id":"c5c1c950-9c8b-42f5-9f56-059b8da0887d","resolution":{"observed_at":"2026-08-07T23:29:04.947606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.917512Z","title":"Robust and fast automatic modulation classification with cnn under multipath fading channels,","venue":null,"work_id":"bc923c85-6acd-47e7-a2a4-38aee9548236","year":2020},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.924549Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:64a552f301ccf14fcb6bed593ee077a557bad5e031485cf68538c19812e74952","observation_id":"1180b924-2ab2-4ab3-89c1-0a1c36af0b4e","resolution":{"observed_at":"2026-08-07T23:29:04.922525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.900731Z","title":"Signet: A novel deep learning framework for radio signal classification,","venue":null,"work_id":"89225656-1631-4dfa-955e-90d27b22fbdc","year":2021},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.929501Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:7705f3ebc5b6fbabb9818c3fe1127ed0f2e5183ea937b4461adfaddaf3da3707","observation_id":"8d9309c9-168b-4a26-8c57-6322b3aaf5de","resolution":{"observed_at":"2026-08-07T23:29:04.905988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.883926Z","title":"Contour stella image and deep learning for signal recognition in the physical layer,","venue":null,"work_id":"da2c2555-ffd1-4f30-b20c-71698962e00d","year":2020},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.934067Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:5503f4db66bcd5694363cbcd2d63bfc43665fc0bbbd0daa057a7e3c0f93a71a6","observation_id":"c4ec6ab4-641a-4601-98a7-aff25efe333d","resolution":{"observed_at":"2026-08-07T23:29:04.889193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.868119Z","title":"Complex-valued networks for automatic modulation classification,","venue":null,"work_id":"68079bde-ee61-4414-a9b3-4a3d4770d996","year":2020},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.938773Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:1cb52f5331bf129be87308057e693537e4a795ee0dcf191f410f87d68faf2a69","observation_id":"92cf1cca-67fc-4f77-8e59-06ada3d450ea","resolution":{"observed_at":"2026-08-07T23:29:04.873159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.852479Z","title":"Semi-supervised learning with generative adversarial networks on digital signal modulation classifica- tion.,","venue":null,"work_id":"664edc94-2eb7-4295-8e6b-b2d2b8a14e18","year":2018},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.943272Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:b69b40ab04b9e6b013cff83281c169c3b09f3be42cf8bb99013f8698d9eee4d7","observation_id":"3a793588-6e4f-4d10-9d55-a3c667b4b56f","resolution":{"observed_at":"2026-08-07T23:29:04.857511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:03.948073Z","title":"Avgnet: Adaptive visibility graph neural network and its application in modulation classification,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.948073Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:0602fcb4fcab2725bb432c51783824182ed163f01f14d315165f1be4187eb423","observation_id":"c6513392-67ff-4964-8e4d-a37fa664cb21","resolution":{"observed_at":"2026-08-07T23:29:03.948073Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.825559Z","title":"Dtsg-net: Dynamic time series graph neural network and it’s application in modulation recognition,","venue":null,"work_id":"c9424c39-5b49-47cf-a660-0abbc1aaff2f","year":2024},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.952905Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:749810f7f99718a460ff58af6660f0bb0ebfd8105eb72b2a7c75c785ec99515e","observation_id":"674d3e8b-333c-493b-92ba-0e609c65712c","resolution":{"observed_at":"2026-08-07T23:29:04.830664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.809797Z","title":"Lstm framework for classification of radar and communications signals,","venue":null,"work_id":"92dd8ff0-0510-4fac-8c68-1fc2cd5e4d5a","year":2023},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.957514Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:bd8f835a49a65f292aad257c093d3627ad4a297129985b66a24ff8d5978919fa","observation_id":"cd9529be-0436-4dc1-b048-410cb6e8419e","resolution":{"observed_at":"2026-08-07T23:29:04.814993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.793656Z","title":"Multi- task learning for radar signal characterisation,","venue":null,"work_id":"611eb092-6eda-4c76-bc86-859c2ccc3f7b","year":2023},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.961914Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:9e1a5e45d18164c2d472e5aecbf465782ac729371404a6950096417a04450b13","observation_id":"aa60d936-e2c3-43d4-ab04-8d5bdb660b46","resolution":{"observed_at":"2026-08-07T23:29:04.798867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:03.966645Z","title":"Wisig: A large-scale wifi signal dataset for receiver and channel agnostic rf fingerprinting,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.966645Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:f2c1380a6c2e706acc2261e33393b48052dd1c92acc4e3f10f5ec78ed223231e","observation_id":"3f18f6fc-6da6-4b31-bed1-3b142f1b4e00","resolution":{"observed_at":"2026-08-07T23:29:03.966645Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.676286Z","title":"Trust in 5g open rans through machine learning: Rf fingerprinting on the powder pawr platform,","venue":null,"work_id":"65c99216-aa50-4ebe-88ae-dcb2cc8587ca","year":2020},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.971314Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:11008a08020a83bc532370db24a3ab2fa63c705227d992e79b60c6066f739774","observation_id":"875feea4-0a5e-4954-95b3-490d92e3970e","resolution":{"observed_at":"2026-08-07T23:29:04.681110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.659953Z","title":"Radio frequency fingerprint identification towards statistical and deep learning features: Review, recent results and future directions,","venue":null,"work_id":"a9aa73ad-5d20-4e50-8ab9-35511cf58c31","year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.976125Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:713ef8e4506ebbeac2ecea23c1a0b1dbb3019754f9f094f590f5759fea970bb3","observation_id":"8a5ef0c9-9d8a-4150-9383-9184395e6441","resolution":{"observed_at":"2026-08-07T23:29:04.665007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.643821Z","title":"Tfmix: A robust time-frequency mixing approach for domain generalization in specific emitter identification,","venue":null,"work_id":"6bc261ee-401a-4039-8f99-de7ea74af7bc","year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.980959Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:8e387c06146eacec0e7594d45b34abeb19953ed53265f63f873fdaaec9f1d86c","observation_id":"0d18b96c-c47d-4dd0-bcd4-888bebce7ebd","resolution":{"observed_at":"2026-08-07T23:29:04.648927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.627287Z","title":"Towards low-complexity wireless technology classification across multiple environments,","venue":null,"work_id":"5b66692e-9ef6-4405-b410-5e4eecdabc50","year":2019},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.987028Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:75295685ba427aaefc94a6c8cd068c53c397235f9a05e67a297d81316d7f693b","observation_id":"cd30b08e-b392-44f6-be38-d1c446aa6828","resolution":{"observed_at":"2026-08-07T23:29:04.632786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.611104Z","title":"Multi-band sub-ghz technology recognition on nvidia’s jetson nano,","venue":null,"work_id":"9cffb4f9-d8e6-42e5-912c-4b21f74058f4","year":2020},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.991633Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:ac4c3bd4f4885fd53feab434a28b849dba7fd51c2551e83fd93393c013e42a8f","observation_id":"e61387f0-3878-4815-a8f5-605ce72781ea","resolution":{"observed_at":"2026-08-07T23:29:04.616022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.595765Z","title":"Wireless interference iden- tification with convolutional neural networks,","venue":null,"work_id":"a88eef77-bb88-46ba-89f0-08258262cd71","year":2017},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:03.996145Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:744216b6f75453d31ccb1a5fdabed5bbaf6b91d2340e6b8766c7ecb2b83442fc","observation_id":"01fd11e9-691e-4de7-a174-9dceb867a7ba","resolution":{"observed_at":"2026-08-07T23:29:04.600631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.580673Z","title":"Deep learning for interference identification: Band, training snr, and sample selection,","venue":null,"work_id":"54942e8a-a73a-424c-a294-b6d9cd311bde","year":2019},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.000406Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:561688ad5eb95b1ad8b46b549510db5d90217c7fdc72d3c01748ac94ba84baa8","observation_id":"835231ff-a09f-4d6a-8bf7-3d371d00776c","resolution":{"observed_at":"2026-08-07T23:29:04.585558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06718","last_updated":"2025-06-20T23:14:19Z","snapshot_observed_at":"2026-08-08T11:37:35.879153Z","submitted_at":"2025-06-07T09:01:38Z","title":"IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.06718","snapshot_observed_at":"2026-08-07T23:29:04.004885Z","title":"Iqfm a wireless foundational model for i/q streams in ai-native 6g,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.004885Z"},"links":{"cited_paper":"/paper/2506.06718","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:efbb907a3bd7e1c86850a89a4313cfb3d3f2017d25e906b50fea34b80aca40df","observation_id":"16102a72-3792-4c3d-8230-4d02c2a76822","resolution":{"observed_at":"2026-08-07T23:29:04.004885Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.564338Z","title":"A foundation model for wireless technology recognition and localiza- tion tasks,","venue":null,"work_id":"8fd84153-81d7-483c-a9d0-44632d498d90","year":2025},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.009709Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:3f707c749a9b6bba706b68da60bd7c1b401809f0ebdd01002b25668a222b4393","observation_id":"4293d2a5-b2fe-4d43-a216-04d8385ae6a8","resolution":{"observed_at":"2026-08-07T23:29:04.570259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.548031Z","title":"Skyllm: Enabling trustworthy uav rf surveillance with foundation models for open-world signal recognition,","venue":null,"work_id":"b9b2c459-12b4-42fe-b7a9-35332d509975","year":2026},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.014108Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:448bab43e1c74a86c278903dad8971301b709b4834b70305bbbce68e91bbb94e","observation_id":"6e1ffada-b9f6-4584-b9a5-219ab81c6472","resolution":{"observed_at":"2026-08-07T23:29:04.553230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.018393Z","title":"Roformer: En- hanced transformer with rotary position embedding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.018393Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:f7d20a45d13e7edf59f5bb8f7a48518a3bde1e834d8cc540e96e51cc5ef1c58c","observation_id":"4c534b17-80f9-406f-ad92-75695ac9c367","resolution":{"observed_at":"2026-08-07T23:29:04.018393Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.519997Z","title":"Go- ing deeper with image transformers,","venue":null,"work_id":"106674b9-dfc7-4932-8ad5-246d2702a473","year":2021},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.023217Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:76ded736117a4de322b046b5f2e777f6cee6d7e39d3714d0df7db87acab5ebdf","observation_id":"a969d7c3-6706-41d0-b001-17a162aeecbf","resolution":{"observed_at":"2026-08-07T23:29:04.524859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.504104Z","title":"Deep networks with stochastic depth,","venue":null,"work_id":"0523694d-c699-44f7-9031-2404fb94fa53","year":2016},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.027601Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:47277001ea8d3294b902358d9ea713160d164994effb53a929ed6acae8858f0a","observation_id":"acea6177-5f88-408b-b40e-3e9d6b129dad","resolution":{"observed_at":"2026-08-07T23:29:04.509184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.032125Z","title":"Toward next-generation signal intelligence: A hybrid knowledge and data-driven deep learning framework for radio signal classification,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.032125Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:088e0827529cc0750c5a1f9f2303ba989ab0ce7f72620e5372e76156900d885b","observation_id":"c6a3a1f3-a81d-49d3-9dc1-7ec0a6c681a8","resolution":{"observed_at":"2026-08-07T23:29:04.032125Z","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":"2026-08-07T23:29:04.036560Z","title":"Over-the-air deep learning based radio signal classification,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.036560Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:6b20264d888aafa18d47a455cd04a1b28262818ca622fa7914e425127515e3f5","observation_id":"3cdff6a4-5c97-4c1c-af21-ef4a91ed7ce9","resolution":{"observed_at":"2026-08-07T23:29:04.036560Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:29:04.468186Z","title":"Dataset for modulation classification and signal type classification for multi-task and single task learning,","venue":null,"work_id":"efa2c6d2-cfe7-41a6-806a-46400db7581f","year":2021},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.040941Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:147861f22b0abd68fef021561a6a0734b307d1ba5e41ba034bc244a6983cb9ff","observation_id":"61b67885-9ea1-46d1-aefb-71fe91957423","resolution":{"observed_at":"2026-08-07T23:29:04.473415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.09918","last_updated":"2022-07-20T14:03:57Z","snapshot_observed_at":"2026-08-06T14:33:30.062319Z","submitted_at":"2022-07-20T14:03:57Z","title":"Large Scale Radio Frequency Signal Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.09918","snapshot_observed_at":"2026-08-07T23:29:04.045536Z","title":"Large scale radio frequency signal classification,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.045536Z"},"links":{"cited_paper":"/paper/2207.09918","citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:46dcf107d35404c19ce2cb82b5a36e6e3c6d5591948211d565ec73c16756e974","observation_id":"558946c5-66d1-403f-8de2-de1ecb20f0cc","resolution":{"observed_at":"2026-08-07T23:29:04.045536Z","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":"2026-08-07T23:29:04.050542Z","title":"Rml22: Realistic dataset generation for wireless modulation classification,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T23:29:04.050542Z"},"links":{"citing_paper":"/paper/2608.05793"},"observation_digest":"sha256:6749185b2ac02f319ee0d80a3fbf6c00b3019b4ccf60a9571a5a00f8b21d2cd8","observation_id":"1aca6fe5-5750-4248-92e6-2e0b07af5487","resolution":{"observed_at":"2026-08-07T23:29:04.050542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.05793","last_updated":"2026-08-06T09:29:19Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-08T12:17:50.538909Z","submitted_at":"2026-08-06T09:29:19Z","title":"Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":24},"total_outbound_references":43},"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 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2608.05793."}