{"as_of":"2026-08-16T09:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:64898b8d108ff2094b72d98304be4acac65af7a44e75f1b2b7d6864718bb9f9e","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:42:12.795046Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2506.19476/citation-record","integrity":"/paper/2506.19476/integrity","json":"/paper/2506.19476/citation-record.json","paper":"/paper/2506.19476"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:42:13.835225Z","title":"Application of machine learning in wireless networks: Key techniques and open issues,","venue":null,"work_id":"dc022ab2-e3a0-4699-9283-a70599117456","year":2019},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.208565Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:7e13e7ff0156c389820260f5350f27af0e9d7faa67610897b683a3d998d8eee6","observation_id":"fa5b78d8-6b49-46a6-8902-2e30ea008842","resolution":{"observed_at":"2026-08-15T18:42:13.842526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.799166Z","title":"Intelligent radio signal processing: A survey,","venue":null,"work_id":"a08315d3-9d88-4419-ac88-3d2b1aa5dde7","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.271829Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:5e2dc5590bcea38a043ed8d05c2d3e281a3eed445da83f94236da893821de214","observation_id":"095b7fa1-aaea-438d-af80-a660b65ba682","resolution":{"observed_at":"2026-08-15T18:42:13.809576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.773279Z","title":"Power of deep learning for channel estimation and signal detection in ofdm systems,","venue":null,"work_id":"e8dce24e-079e-49e3-827e-a355b5548e17","year":2017},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.306216Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:6f44da203c213e3a92a8b88ad5a830a2041349b2c8fe1586afce0e1bcd4c16e7","observation_id":"d53243c4-3389-40fe-8c6e-b9dcc66ec123","resolution":{"observed_at":"2026-08-15T18:42:13.780610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.747961Z","title":"Deep learning for joint channel estimation and signal detection in ofdm systems,","venue":null,"work_id":"c326f82a-0d4a-4b9e-98bc-c392b0d4c1f7","year":2020},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.313570Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:14bb1e3fe17868f94c7278ba3c43b86e81666e15f6aba2be46475423b55caf30","observation_id":"0b10642b-38bd-47ac-bfff-53380ed41fbd","resolution":{"observed_at":"2026-08-15T18:42:13.755369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.716905Z","title":"Deep learning-based end-to- end wireless communication systems with conditional gans as unknown channels,","venue":null,"work_id":"e2459eda-493d-4f5c-b5e5-b23ed911e453","year":2020},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.322677Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:1a6551f98664b891b2d4774b3bd4e64cc6de19df8ca9a9e606670d863e19f976","observation_id":"b16bceef-088b-4478-90f2-52e5daa3d209","resolution":{"observed_at":"2026-08-15T18:42:13.727289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.692705Z","title":"Deep learning based end-to-end wireless communication systems without pilots,","venue":null,"work_id":"e9d9f1b0-b4e7-4148-8dab-863d6ba47fed","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.330667Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:e1ca40cf9258ac7672f905bfee93b29e9425674c20907978f74c7d9f41e2a1f6","observation_id":"cbe178e4-d55b-48a6-a0ff-d12894645c09","resolution":{"observed_at":"2026-08-15T18:42:13.700297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.668470Z","title":"Deeprx: Fully convolutional deep learning receiver,","venue":null,"work_id":"f703ff05-5c17-419f-ba0c-578391d4e498","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.339071Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:a0e8ba06469e16376238cb85c2fd3ea5d782aad37c6157bf1f33e5cccead3b76","observation_id":"42724d38-d2e8-4cc0-b726-6010dd493178","resolution":{"observed_at":"2026-08-15T18:42:13.675655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.08707","last_updated":"2025-02-12T13:29:11Z","snapshot_observed_at":"2026-08-12T23:02:38.115133Z","submitted_at":"2024-08-16T12:40:01Z","title":"Beam Prediction based on Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08707","snapshot_observed_at":"2026-08-15T18:42:12.350771Z","title":"Beam predic- tion based on large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.350771Z"},"links":{"cited_paper":"/paper/2408.08707","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:c950d8cb3f21eb482530eb8b6b7e6bfe186ba1b38d8b2a5c290ff320f0b95b52","observation_id":"69cee451-9cef-44f7-8939-5e93363c809e","resolution":{"observed_at":"2026-08-15T18:42:12.350771Z","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":"2026-08-15T18:42:13.642086Z","title":"Communication-efficient learning of deep networks from decentralized data,","venue":null,"work_id":"058ed5cc-eeb1-4761-a9f5-0e9a7ba6b2fa","year":2017},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.358019Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:bcd810e9d68d53adcf84a8c0a7e33cdbd334732f9d9df46ddd31168adffa6f01","observation_id":"111f59fd-ca16-4e88-9ab6-43a2904e2dc9","resolution":{"observed_at":"2026-08-15T18:42:13.652531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.618582Z","title":"Federated learning and wireless commu- nications,","venue":null,"work_id":"65416ac9-7ebb-48ef-8586-8ff1e8adb40d","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.366162Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:ee43e936808dd30faff45c5e7704ead0a34499708480c26b2f033a9cd2c3d855","observation_id":"d10b2a59-8d17-467f-a72e-f0f61b8a2220","resolution":{"observed_at":"2026-08-15T18:42:13.625917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.592099Z","title":"Federated reinforcement learning for resource allocation in v2x networks,","venue":null,"work_id":"ec804631-e7d2-4ee0-9b19-0a57bce920d0","year":2024},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.378061Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:afadff7b527288086d3f66e66a2e2a5ba3035ab9c5176722752b0b129eb6bed7","observation_id":"f4ef0633-e359-4816-83e8-45efd48040cb","resolution":{"observed_at":"2026-08-15T18:42:13.598936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.560122Z","title":"Rescale-invariant federated reinforce- ment learning for resource allocation in v2x networks,","venue":null,"work_id":"93b81edd-8be8-40c5-adfa-b2d1df4e5b7c","year":2024},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.387145Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:5dd4d68c456b5e7c89f9ba23dc298e8f3d7bee51e9dccd9c616c343c822549b3","observation_id":"bec7b1ee-f033-49cb-b790-fe34f2eade35","resolution":{"observed_at":"2026-08-15T18:42:13.569825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12343","last_updated":"2023-10-18T21:42:37Z","snapshot_observed_at":"2026-08-13T05:45:52.056132Z","submitted_at":"2023-10-18T21:42:37Z","title":"New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming","version":1},"cited_work":{"arxiv_id":"2310.12343","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.12343","snapshot_observed_at":"2026-08-15T18:42:13.003050Z","title":"New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming","venue":"cs.DC","work_id":"98809489-6d26-49d7-8a5e-db11e6b0284a","year":2023},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.395713Z"},"links":{"cited_paper":"/paper/2310.12343","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:a0c01fe152f394b1f880acaa12c03f9ed8b41fede83d1cd57f4d8a4acb848b35","observation_id":"f477193a-27be-442d-aa47-b5d9b3f48517","resolution":{"observed_at":"2026-08-15T18:42:13.013187Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:12.406852Z","title":"Federated optimization in heterogeneous networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.406852Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:6d943f90d51a2350a357f5b7e713b5a39c74686c9aba1a1867f49ad848384c72","observation_id":"cf401799-d064-4b51-ae06-3ee8e53a6e60","resolution":{"observed_at":"2026-08-15T18:42:12.406852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15486","last_updated":"2025-01-26T11:17:32Z","snapshot_observed_at":"2026-08-10T22:51:09.904079Z","submitted_at":"2025-01-26T11:17:32Z","title":"FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15486","snapshot_observed_at":"2026-08-15T18:42:12.415839Z","title":"Fedalign: Federated do- main generalization with cross-client feature alignment,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.415839Z"},"links":{"cited_paper":"/paper/2501.15486","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:da8d06aabbf7498adc0a0d4e76a347aeacb878fc8b331c0240ef3e403a764355","observation_id":"d8b14bc9-1f88-493c-bf1f-a3faa0c404f5","resolution":{"observed_at":"2026-08-15T18:42:12.415839Z","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":"2026-08-15T18:42:13.484921Z","title":"Model-contrastive federated learning,","venue":null,"work_id":"6c1c40d2-de1e-4a16-9591-f3cd5e6b86b6","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.425435Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:2f3a09097158aa2b1fe8e7d8ae1a20779c26aca9fa1b640246fd8db31e17f6c6","observation_id":"2790c05e-b25a-4023-adc6-72f8549fa4f6","resolution":{"observed_at":"2026-08-15T18:42:13.498275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.456272Z","title":"Federated learning with matched averaging,","venue":null,"work_id":"46230199-e4ec-4e34-be78-e5e161e4d9b3","year":2020},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.437530Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:9ba4ee9a1192c90aaa5b463385180c6ed2ea1f397c1f5017b75b0bb573fa74c1","observation_id":"0a5a1ff4-2c86-4bc5-a184-f3a94c02451a","resolution":{"observed_at":"2026-08-15T18:42:13.465690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.408988Z","title":"Prevalence of neural collapse during the terminal phase of deep learning training,","venue":null,"work_id":"750fa199-7ff4-473d-a4b4-a8f3f4b4b87d","year":2020},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.446960Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:68de3a666c3d093f0b1dfd4f0ef24d08dd78f40178174cff93f869715a62aa71","observation_id":"b699ac51-1fd0-4c55-b4a1-8106e099202b","resolution":{"observed_at":"2026-08-15T18:42:13.418602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.386248Z","title":"Neural collapse: A review on modelling principles and generalization,","venue":null,"work_id":"b711f06f-f7bc-4c90-a55d-ca60d0a36ec2","year":2023},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.456196Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:728f05b4034e29acea5bc5f96e9c9b2038add3b6a13d025617e8d16f6c2dbe27","observation_id":"af113766-9206-499b-aaa7-882b6b57ab6f","resolution":{"observed_at":"2026-08-15T18:42:13.393976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.356709Z","title":"A geometric analysis of neural collapse with unconstrained features,","venue":null,"work_id":"c6fffce3-801c-4eb8-8b11-00bb81f6e169","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.464555Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:ceaea76097cc1786b7eb942e7eb5cd3cee0d88e5edb4845edecc2572018a1ebe","observation_id":"220aabf4-b2ef-49ea-b49e-4e5d99128228","resolution":{"observed_at":"2026-08-15T18:42:13.363058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.333767Z","title":"Memorization-dilation: Modeling neural collapse under noise,","venue":null,"work_id":"ebbd2aac-df2e-494f-862b-aa66a05c1516","year":2023},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.469969Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:00c0d3a88ebf31341338ce48853583af5047710b09a6495038d2e8bf0ce745a9","observation_id":"e8975473-b48c-4dda-8347-3fd405a9eae5","resolution":{"observed_at":"2026-08-15T18:42:13.340800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.299942Z","title":"Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?","venue":null,"work_id":"3e35ab64-68b8-4b2c-817d-c2b184cc9c40","year":2022},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.491860Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:a3e1a661a98334496273e1c9f0e79b2887f13419bb3fd0f152e646c27c1026ca","observation_id":"cbdbc595-62c2-437b-8b5d-b7cc87dd3d75","resolution":{"observed_at":"2026-08-15T18:42:13.308091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.15903","last_updated":"2024-06-20T09:18:01Z","snapshot_observed_at":"2026-08-13T05:42:06.458412Z","submitted_at":"2023-10-24T15:07:16Z","title":"Neural Collapse in Multi-label Learning with Pick-all-label Loss","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.15903","snapshot_observed_at":"2026-08-15T18:42:12.552569Z","title":"Neural collapse in multi-label learning with pick-all-label loss,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.552569Z"},"links":{"cited_paper":"/paper/2310.15903","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:12307993ef4ccc093a18fde297208721e995ff74216dd7c6cac976239036f46a","observation_id":"b9930a52-9488-420b-88db-c1255989495d","resolution":{"observed_at":"2026-08-15T18:42:12.552569Z","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":"2026-08-15T18:42:13.273151Z","title":"The prevalence of neural collapse in neural multivariate regression,","venue":null,"work_id":"4a3defda-4f61-4247-96bb-0d78392dfa94","year":2024},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.696522Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:0bb80fe53d22abdec8e76f0d56cbe45287646e81f6d37e4ab73b4113beb11c46","observation_id":"60cf0faa-3aa4-45e3-944b-fa6aef62db14","resolution":{"observed_at":"2026-08-15T18:42:13.281045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.240854Z","title":"Deeply-supervised nets,","venue":null,"work_id":"715ada04-4bac-4cfc-8817-8c6a9f55b63f","year":2015},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.743816Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:94c55e75cc8a9b0f2a64329b8471c69b65e11cc59cd2f3184a0dbdafda5abaef","observation_id":"459f1603-77b1-47b9-9125-2793ae317217","resolution":{"observed_at":"2026-08-15T18:42:13.253210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.02376","last_updated":"2022-07-06T00:56:06Z","snapshot_observed_at":"2026-08-13T23:08:11.163681Z","submitted_at":"2022-07-06T00:56:06Z","title":"A Comprehensive Review on Deep Supervision: Theories and Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.02376","snapshot_observed_at":"2026-08-15T18:42:12.750230Z","title":"A comprehensive review on deep su- pervision: Theories and applications,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.750230Z"},"links":{"cited_paper":"/paper/2207.02376","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:fc7d078def3eb630ebdbde3486132c15f4e4b3fe009d4f1a7e37e7cae273ee68","observation_id":"6d0f2da8-cdd5-4d08-813f-bff5f50addde","resolution":{"observed_at":"2026-08-15T18:42:12.750230Z","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":"2026-08-15T18:42:13.206019Z","title":"3d deeply supervised network for automatic liver segmentation from ct volumes,","venue":null,"work_id":"2f5a8260-3318-46ab-bf8a-b5126753a829","year":2016},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.757014Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:8b6371c3d094925d3f0a20b32b0393cb395fc865b2bf38cf3ff8d21e835c4830","observation_id":"ab7975f4-aa0b-46b7-baa2-2110e45e0259","resolution":{"observed_at":"2026-08-15T18:42:13.213920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.180676Z","title":"Sne-roadseg+: Rethinking depth- normal translation and deep supervision for freespace detection,","venue":null,"work_id":"b3a5ca02-61ed-4be5-a037-d6fdfa278138","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.764303Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:34741eac94ebdd30019ebce696f1a94bead10829e31ef12fa003b6bd2ab3a808","observation_id":"1f2152bc-2cb4-4d4a-8130-07a5c2f192e9","resolution":{"observed_at":"2026-08-15T18:42:13.189112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.145700Z","title":"Deeply-recursive convolutional network for image super-resolution,","venue":null,"work_id":"b0fc08ba-cdab-42f5-982b-0cc472ae9dbc","year":2016},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.772490Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:b0ef69285d0a1b8f3c19de20db389095c2a5f8c0ab533d2bf26b37a229a81874","observation_id":"9cfdb87e-3cc7-465e-a525-742b6b63e101","resolution":{"observed_at":"2026-08-15T18:42:13.155338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T18:42:13.114301Z","title":"Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training,","venue":null,"work_id":"798216f9-25c9-4b88-aa8d-f29824ba825e","year":2021},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.778913Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:ed23a478ccf3b551df97db788f2753aa2cd35730f58c5373675b0625d390b32c","observation_id":"dc09d883-e2a9-498e-bb28-13cb115ecee6","resolution":{"observed_at":"2026-08-15T18:42:13.125831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-14T18:51:16.666127Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-15T18:42:12.787327Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.787327Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:11b17757b8fda09a3bde22e078a9bfebe7b929b1139fbc3341c47ad0eb3890c0","observation_id":"0b4d8c7b-727e-4290-b99a-7d24b570e400","resolution":{"observed_at":"2026-08-15T18:42:12.787327Z","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":"2026-08-15T18:42:13.080355Z","title":"Winner ii channel models,","venue":null,"work_id":"cb511ebd-0c99-4dbd-8365-686b14c0a384","year":2007},"citing_paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T18:42:12.795046Z"},"links":{"citing_paper":"/paper/2506.19476"},"observation_digest":"sha256:bd66060209a671832b0f423bd78f2aad509d57f200d098a523d320625763c224","observation_id":"a0e63730-2668-4945-8fc2-2e8deb3e10fd","resolution":{"observed_at":"2026-08-15T18:42:13.095669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.19476","last_updated":"2025-06-24T10:03:11Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-16T00:29:39.839471Z","submitted_at":"2025-06-24T10:03:11Z","title":"Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":25},"total_outbound_references":32},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.19476."}