{"as_of":"2026-08-07T19:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fa505616b2b26781c53918787aba876b5287ef9f24d27fd797865e2d8ec0430e","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-24T15:46:59.992223Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/1907.11294/citation-record","integrity":"/paper/1907.11294/integrity","json":"/paper/1907.11294/citation-record.json","paper":"/paper/1907.11294"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Millimeter Wave mobile communications for 5G cellular: it will work!","venue":null,"work_id":"c8cae5c4-956f-45c4-a5fe-4e0ea3ad5acf","year":2013},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:73f7144b1d2ffd51a306cb6fb8ac4f46e7a3f91efababdb3c1e52acd69304e68","observation_id":"06df9469-2cb7-4c25-8375-83c597917fbd","resolution":{"observed_at":"2026-05-24T15:49:41.315964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Millimeter wave channel modeling and cellular capacity evaluation","venue":null,"work_id":"026a045e-e6cc-424d-ad4e-edbebaccd044","year":2014},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:a5bf833d007ee7bff876dd956c4743a66ee0a8b1fc95e44c0463d269da38f91b","observation_id":"5d2fae8a-bb25-47a4-9a82-fc154c0c59f7","resolution":{"observed_at":"2026-05-24T15:49:41.320474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"An introduction to deep learning for the physical layer","venue":null,"work_id":"17b9955b-257d-4d04-bf97-82413d14b7da","year":2017},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:d733b65b8d2a2dcf3d435ced3d41f4ad812cbfd5f777d54ba4aba4f47abc4657","observation_id":"fdc133ae-a916-482d-8dfb-7e58c8b6268a","resolution":{"observed_at":"2026-05-24T15:49:41.308383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep learning for intelligent wireless networks: A comprehensive survey","venue":null,"work_id":"aca874f1-4c6c-4412-9682-1a8dcf9daba5","year":2018},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:25f576f3b2408f745616fe2c4f52d9a0bc0db0923238c28fbdb8fb81f7f51b93","observation_id":"fea33a13-9a9c-407d-b063-c871c30af0c1","resolution":{"observed_at":"2026-05-24T15:49:41.361258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A very brief introduction to machine learning with appli- cations to communication systems","venue":null,"work_id":"d5c390a1-6a35-46b0-9a90-7ff1b7d60c77","year":2018},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:0fd2215076c606cb4276017ea967ba64b80247af3fe297ddd0ccea3e1c0b3dd3","observation_id":"1c581de4-b88b-4e87-82a2-e0a8613d4b12","resolution":{"observed_at":"2026-05-24T15:49:41.366394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning to decode linear codes using deep learning","venue":null,"work_id":"4b4f392c-ed5f-4a53-90b8-b716340cb980","year":2016},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:47e1e27976ef56194b7c68dcc526dee4675298eb7969c6ab6f99fa0a12681dc7","observation_id":"bf0ea5e8-fae2-485d-8294-1f85fcf1f3d2","resolution":{"observed_at":"2026-05-24T15:49:41.348336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning to communicate: Channel auto-encoders, domain specific regularizers, and attention","venue":null,"work_id":"16395eda-71b1-41f3-b3ce-46d87e4c9f57","year":2016},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:fcecdb246d340f8e18527b8efa6075f4ed9339f0820896a3720c4d67f9364f55","observation_id":"564c0085-0ee2-4c01-8607-7cdb802b7bd0","resolution":{"observed_at":"2026-05-24T15:49:41.352016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ViterbiNet: Symbol detection using a deep learning based Viterbi algorithm","venue":null,"work_id":"ee08e5ae-de47-4547-a292-bfe38e60d079","year":2019},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:14f43cb2feef997d1a363cb84db964f166f63f5684890ab60e0a9a5445364a7a","observation_id":"c73a7fc9-77bf-43c9-9c1b-bd0126dd6867","resolution":{"observed_at":"2026-05-24T15:49:41.356642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural network detection of data sequences in communication systems","venue":null,"work_id":"69bf74b1-95a6-450a-adad-af36234cbd89","year":2018},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:10da9abcea536899ed797ebdb991552a3bbe31e75bd428fe63e8a684db23dda4","observation_id":"0dedb531-eb16-472c-b796-65fd4c345c45","resolution":{"observed_at":"2026-05-24T15:49:41.340811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Predicting wireless mmWave massive MIMO channel characteristics using machine learning algo- rithms","venue":null,"work_id":"bfe1ee60-1491-4209-835a-130b15472301","year":2018},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:26df40b2aa9e8feb35086e5912ef9fb452a8e2dab187f8e14e4e75e10eba8a28","observation_id":"45d4e130-dcce-4c1c-a3da-37cca6ad08d0","resolution":{"observed_at":"2026-05-24T15:49:41.344821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.06537","last_updated":"2019-01-19T15:02:30Z","snapshot_observed_at":"2026-07-06T07:27:40.785901Z","submitted_at":"2019-01-19T15:02:30Z","title":"Deep-Learning-based Millimeter-Wave Massive MIMO for Hybrid Precoding","version":1},"cited_work":{"arxiv_id":"1901.06537","doi":null,"metadata_source":"pith","pith_arxiv_id":"1901.06537","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep-Learning-based Millimeter-Wave Massive MIMO for Hybrid Precoding","venue":"eess.SP","work_id":"2c8f8001-2b22-448a-b6b1-55660696549f","year":2019},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"cited_paper":"/paper/1901.06537","citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:c9d036c8a4be933a674da17cbef76536c0af559788568e485969a39ada4829e9","observation_id":"fff5532c-c7fa-4a34-9967-22884c23eb1c","resolution":{"observed_at":"2026-05-24T15:49:39.786789Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep learning-based beam management and interference coordination in dense mmWave networks","venue":null,"work_id":"6845fbb1-7931-4a93-98ed-f4e129a109d6","year":2019},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:2f6d2bc3dbe54d4de92aceb9d7774c78031107bdf6b442ce5be9c8e0153d7c40","observation_id":"1f6a0bd2-8c19-4eb1-aa45-f7d99461bf22","resolution":{"observed_at":"2026-05-24T15:49:41.376526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Noncooperative cellular wireless with unlimited numbers of base station antenna","venue":null,"work_id":"182c41a1-acfa-4a21-9784-e75a33a70266","year":2010},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:cab78cb483dbbbc3a99e2f8baa25de0df300efb78f3b976bf065ad5a7c0a1fb5","observation_id":"b4a8c46c-319f-4141-a2a5-bfa1fb06a3cc","resolution":{"observed_at":"2026-05-24T15:49:41.334332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"225c943c-d185-4885-b1ea-95ac989cfc65","year":1998},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:b001d14022b5771dec278bba9958c84bb50d62bca864ad3488a22898eef57128","observation_id":"060e96c7-ed8c-448e-b617-5308e89a0767","resolution":{"observed_at":"2026-05-24T15:49:41.330613Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3-D millimeter-wave statistical channel model for 5G wireless system design","venue":null,"work_id":"b0716329-0f77-41a6-b573-d60401d3592b","year":2016},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:973d355e8d7b9234123abe6517790a2d689960f69a96846c5a4b6fc5cff0be9d","observation_id":"0ac3a4c2-ed16-4851-b6bf-b2f144f81d0a","resolution":{"observed_at":"2026-05-24T15:49:41.372570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Study on channel model for frequencies from 0.5 to 100 GHz simulations","venue":null,"work_id":"551a43a1-3adc-44c1-a966-cbc0852a3663","year":2018},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:5d6f521e511dbd97693a32c0451ee6ad0df5d1e6feda22ae0f44dab056e237b2","observation_id":"31a6fe47-c526-4cd3-91ec-308c5b6b2868","resolution":{"observed_at":"2026-05-24T15:49:41.380853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficient Viterbi beam search algorithm using dynamic pruning","venue":null,"work_id":"946610a3-d669-4bc0-984c-363a44156a86","year":2004},"citing_paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-24T15:46:59.992223Z"},"links":{"citing_paper":"/paper/1907.11294"},"observation_digest":"sha256:d8d316c08b70bf5fc9fec47606f16439e9aa04722a480bc4aedfc3fe61eaf545","observation_id":"31e2c275-9c97-451c-819f-4605b6cc43e8","resolution":{"observed_at":"2026-05-24T15:49:41.325071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1907.11294","last_updated":"2019-07-25T20:06:32Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-02T19:02:30.108343Z","submitted_at":"2019-07-25T20:06:32Z","title":"Deep Neural Network Symbol Detection for Millimeter Wave Communications"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":15},"total_outbound_references":17},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:1907.11294."}