{"as_of":"2026-08-09T17:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f363ccf9bed6a218d1d7768abc9c8a1a92f10635e098aa192dcc296b24399f47","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T10:13:22.349862Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2510.11214/citation-record","integrity":"/paper/2510.11214/integrity","json":"/paper/2510.11214/citation-record.json","paper":"/paper/2510.11214"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T10:13:18.724471Z","title":"Biglieri, R","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:18.724471Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:e1c832b903de4762db7ceddac7b76327bffb4f9baf3d461a808631c5a280b00b","observation_id":"3232b87c-7542-4126-b720-3f648c79cdac","resolution":{"observed_at":"2026-08-04T10:13:18.724471Z","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":"2026-08-04T10:13:18.827583Z","title":"How much training is needed in multiple-antenna wireless links?","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:18.827583Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:9c275c2bc4d6e7102a00cc71d69153369cd88408b602b882ec074d6cc9be415d","observation_id":"b1e21dd9-eabb-433a-881f-2e80f3e48d57","resolution":{"observed_at":"2026-08-04T10:13:18.827583Z","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":"2026-08-04T10:13:18.966037Z","title":"Five disruptive technology directions for 5G,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:18.966037Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:ee4280ef627986b167ce1430888481000837ec6df5232094bda3921fa7b886c0","observation_id":"2837fc66-2290-4e93-82df-40fa2dee39f5","resolution":{"observed_at":"2026-08-04T10:13:18.966037Z","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":"2026-08-04T10:13:19.083656Z","title":"Channel estimation and hybrid precoding for millimeter wave cellular systems,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.083656Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:f1e6f1b5a0f6c91fc289553a376229b218ab8cac5ab2982a9c70469cf6fc875a","observation_id":"281a4ba5-77ea-434c-acbc-156968ad6bcd","resolution":{"observed_at":"2026-08-04T10:13:19.083656Z","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":"2026-08-04T10:13:19.207509Z","title":"Towards systems beyond 3G based on adaptive OFDMA transmission,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.207509Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:e62158dd9ae78e7c66841416f5794606cea8297b155e7f0c595bd73c2e027e16","observation_id":"02fe6574-5bda-4216-989e-01c008583abc","resolution":{"observed_at":"2026-08-04T10:13:19.207509Z","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":"2026-08-04T10:13:19.247788Z","title":"Addressing the curse of mobility in massive MIMO with prony-based angular-delay domain channel predictions,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.247788Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:b4b878fc5a982a67e0a3a0ad65e67dd14a25737a694582e052b33b99ea74ea15","observation_id":"18767132-6066-40f1-b2fa-1d34a2147997","resolution":{"observed_at":"2026-08-04T10:13:19.247788Z","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":"2026-08-04T10:13:19.250818Z","title":"Massive MIMO channel prediction: Kalman filtering vs. machine learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.250818Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:bc7cbfd2ae730c38362e8c6bf79ee4859a2b531b25c7e8ae085ea106de95bbb4","observation_id":"b67996de-240a-4da6-b62b-d758ca8e173e","resolution":{"observed_at":"2026-08-04T10:13:19.250818Z","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":"2026-08-04T10:13:19.315929Z","title":"Joint channel estimation and prediction for OFDM systems,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.315929Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:7f00a63cc8fe6c6afb9c0370ac63b54b32e551edfe8a1951366e926a752eccc6","observation_id":"ecc33f6b-3586-44b1-9574-f1452d20ef99","resolution":{"observed_at":"2026-08-04T10:13:19.315929Z","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":"2026-08-04T10:13:19.425423Z","title":"Spatial wireless channel prediction under location uncertainty,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.425423Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:7cfc999c3e06c29544bc9874bb0234dbf70dc302a3581b6349d82b53aafc8bc4","observation_id":"d04f5b36-ba5d-4b18-aef7-4f01f2b067c0","resolution":{"observed_at":"2026-08-04T10:13:19.425423Z","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":"2026-08-04T10:13:19.492744Z","title":"Predictor antenna: A technique to boost the performance of moving relays,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.492744Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:534742864e72c25e1e13f0f114bcc7adcec92f78ce132d2a4a79f08c81bf0a35","observation_id":"55b34a06-e37a-4b93-9adb-c1f0b7a402bb","resolution":{"observed_at":"2026-08-04T10:13:19.492744Z","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":"2026-08-04T10:13:19.603079Z","title":"Autoregressive modeling for fading channel simulation,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.603079Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:126cd918364c7433b295303b833aaa87889a7ba37a59ea795cc4c8d9d04414cb","observation_id":"19064426-e683-4b05-bd6d-e83479c4b4e9","resolution":{"observed_at":"2026-08-04T10:13:19.603079Z","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":"2026-08-04T10:13:19.677893Z","title":"Deep learning with long short-term memory networks for financial market predictions,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.677893Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:7386cf071f7b4d3a554911e4383b6b5fb71378b9b8fc5c1ed86b8f9826c83049","observation_id":"8bfc164f-d269-499a-9192-8810168a5359","resolution":{"observed_at":"2026-08-04T10:13:19.677893Z","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":"2026-08-04T10:13:19.738308Z","title":"Short-term residential load forecasting based on LSTM recurrent neural network,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.738308Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:9b65047c0f38a12f8644fa29418714f06e8dbdfa4efe00dc8473e742a707263a","observation_id":"5f34472f-b04b-43cd-bb32-84292d35c913","resolution":{"observed_at":"2026-08-04T10:13:19.738308Z","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":"2026-08-04T10:13:19.793823Z","title":"Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.793823Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:b4e8747871e49698b8465eb7a2fb4eab846e14d883c324a6c8130bd61317d5e3","observation_id":"ed696063-fcd8-4177-98f0-27b794a95af6","resolution":{"observed_at":"2026-08-04T10:13:19.793823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03006","last_updated":"2024-01-17T14:02:12Z","snapshot_observed_at":"2026-07-06T17:12:10.787061Z","submitted_at":"2024-01-05T11:35:10Z","title":"The Rise of Diffusion Models in Time-Series Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03006","snapshot_observed_at":"2026-08-04T10:13:19.868738Z","title":"The rise of diffusion models in time-series forecasting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.868738Z"},"links":{"cited_paper":"/paper/2401.03006","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:bc180c7ce2dadaba0c70e87dd91d6cfedef71423b2bdebd59f168960d489dfa1","observation_id":"2158a027-9332-4748-9e33-66282d49a341","resolution":{"observed_at":"2026-08-04T10:13:19.868738Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-08-04T10:13:19.945980Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.945980Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:e6ad74b241492470f3547c60ff7ba89f15dbba921507f31dea287fb0acebfe9a","observation_id":"884100ef-83b0-4cfb-a1c2-2aade4c0325f","resolution":{"observed_at":"2026-08-04T10:13:19.945980Z","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":"2026-08-04T10:13:20.083770Z","title":"Channel prediction in high-mobility massive MIMO: From spatio-temporal autoregression to deep learning,","venue":null,"work_id":null,"year":1915},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.083770Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:e95405637e6d3116d9f1e45b2d06bde74216dfc21240e94bb78438f0b1a6a42a","observation_id":"bcaa9b56-e30d-4c16-b130-238324bae654","resolution":{"observed_at":"2026-08-04T10:13:20.083770Z","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":"2026-08-04T10:13:20.161743Z","title":"A comparison of neural networks for wireless channel prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.161743Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:df8d54c74218e15acc8652067a338f361271458dceae4ccaa19bcf11364560a4","observation_id":"83af4f63-dd64-4311-8057-46460f73e697","resolution":{"observed_at":"2026-08-04T10:13:20.161743Z","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":"2026-08-04T10:13:20.268627Z","title":"Spatio- temporal neural network for channel prediction in massive MIMO- OFDM systems,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.268627Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:aef2daf6375afff9e090dc100b54821ad351cd1736202ab77675af438ba746a6","observation_id":"09f139b9-f84c-422a-8863-f72191d1eb56","resolution":{"observed_at":"2026-08-04T10:13:20.268627Z","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":"2026-08-04T10:13:20.355753Z","title":"Recurrent neural network-based frequency-domain channel prediction for wideband communications,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.355753Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:83efa4b63179984af6e5ffa804db85a4e21b06c240dd3cb95881c8d82b1bd341","observation_id":"2586322b-e82a-4a4a-88a8-186bf0423fa6","resolution":{"observed_at":"2026-08-04T10:13:20.355753Z","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":"2026-08-04T10:13:20.451328Z","title":"Deep learning for fading channel prediction,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.451328Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:66bd3514f363fd36c3f762c508937a576675bf5d872ac0458f7fd94e722b8802","observation_id":"baa945f3-459e-4f95-992a-a23f82083a62","resolution":{"observed_at":"2026-08-04T10:13:20.451328Z","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":"2026-08-04T10:13:20.567086Z","title":"CSI-LLM: A novel downlink channel prediction method aligned with LLM pre-training,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.567086Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:2d2e5e23d8731644f885f11db50b0a4e256877e40ae542e1972a864f595058f3","observation_id":"5d7038de-2029-4cea-9d3e-b2ef019d4a9e","resolution":{"observed_at":"2026-08-04T10:13:20.567086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18196","last_updated":"2025-02-25T13:37:20Z","snapshot_observed_at":"2026-08-09T03:28:27.153249Z","submitted_at":"2025-02-25T13:37:20Z","title":"Machine Learning for Future Wireless Communications: Channel Prediction Perspectives","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.18196","snapshot_observed_at":"2026-08-04T10:13:20.634051Z","title":"Machine learning for fu- ture wireless communications: Channel prediction perspectives,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.634051Z"},"links":{"cited_paper":"/paper/2502.18196","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:9fd16c13e34e817db92ef4ccaefc10dd9a4086ca354db6db39b46d45694b48ac","observation_id":"0f40f80d-6ae2-4869-8796-5074546ee662","resolution":{"observed_at":"2026-08-04T10:13:20.634051Z","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":"2026-08-04T10:13:20.727612Z","title":"Time- varying channel prediction for RIS-assisted MU-MISO networks via deep learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.727612Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:78f9dfa655750d061d24b22309b86c1b7178b57c752fe0e59d019a4f9cdcf73e","observation_id":"1a726fb8-7919-4253-88d6-5f7440c57ef0","resolution":{"observed_at":"2026-08-04T10:13:20.727612Z","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":"2026-08-04T10:13:20.778368Z","title":"Accurate channel prediction based on transformer: Making mobility negligible,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.778368Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:034a6fdd38dd80cc032f038273837c2e17fda5ed62d2d064a2e847637ff15e44","observation_id":"8ba135e7-7a85-4788-b755-24389d966323","resolution":{"observed_at":"2026-08-04T10:13:20.778368Z","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":"2026-08-04T10:13:20.841355Z","title":"Linformer: A linear-based lightweight transformer architecture for time-aware MIMO channel prediction,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.841355Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:b1a68a44f8dcbabee09edbc3cb7e4e72ad670a05db932c9d2e1d6ad37e9c2eda","observation_id":"2159690a-3fb6-4d7f-b574-a676cdd31fe2","resolution":{"observed_at":"2026-08-04T10:13:20.841355Z","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":"2026-08-04T10:13:20.898619Z","title":"Enhancing reliability in AI-based CSI prediction: A proxy-based performance monitoring ap- proach,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.898619Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:56f0f96e89263a0fd4ab359b35fcb1032926ceb8ec501eea04df6914a43b8769","observation_id":"29d77e22-c100-4e82-b07e-5edaf0e471f7","resolution":{"observed_at":"2026-08-04T10:13:20.898619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.11072","last_updated":"2024-05-17T20:03:10Z","snapshot_observed_at":"2026-07-06T18:16:03.617132Z","submitted_at":"2024-05-17T20:03:10Z","title":"Next-slot OFDM-CSI Prediction: Multi-head Self-attention or State Space Model?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.11072","snapshot_observed_at":"2026-08-04T10:13:20.993490Z","title":"Next-slot OFDM- CSI prediction: Multi-head self-attention or state space model?","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:20.993490Z"},"links":{"cited_paper":"/paper/2405.11072","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:fa98c17df979bb41636b20e19c50ef2447f3f6061909766040688bd883a0b6ae","observation_id":"5302bd7b-f141-4a4c-85e9-b0c2e49e92d0","resolution":{"observed_at":"2026-08-04T10:13:20.993490Z","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":"2026-08-04T10:13:21.055894Z","title":"Reverse ordering techniques for attention-based channel prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.055894Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:f162c01fbc10a5fa80fd78a367034c7ecd3313cdec8596f1699c4c413718d7dc","observation_id":"893e3f2c-0b5d-4436-8acd-34b2fe40be0e","resolution":{"observed_at":"2026-08-04T10:13:21.055894Z","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":"2026-08-04T10:13:21.113388Z","title":"CSI-BERT2: A BERT-inspired framework for efficient CSI prediction and classification in wireless communication and sensing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.113388Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:e5f098180a3895d36fee6670620c0de267255a86fa7486c397d77f3003cdc8b1","observation_id":"7295029e-94a7-4d36-bbed-c80ff32a463a","resolution":{"observed_at":"2026-08-04T10:13:21.113388Z","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":"2026-08-04T10:13:21.189825Z","title":"Spectral temporal graph neural network for massive MIMO CSI prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.189825Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:fc011d60e497f9bd67271de8151f716dee2646d212a9e54566da3030f1713ca4","observation_id":"dbcf9f68-be1b-48e8-8151-5073322ca3cd","resolution":{"observed_at":"2026-08-04T10:13:21.189825Z","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":"2026-08-04T10:13:21.259510Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.259510Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:2f3cc2e3dca420a98d9f766db72ac606149d97074dd08c5750137e2166e6fc78","observation_id":"3b275479-c4ed-45f7-9c41-3333eb538eb5","resolution":{"observed_at":"2026-08-04T10:13:21.259510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-04T10:13:21.353472Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.353472Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:868a4bfe0ca14a559ae0a7e644bda4b518bc8fa25ddd0d2e5374dd2e5ad99ede","observation_id":"d1c3ad1f-3224-4d2d-8866-c063a0d2ac89","resolution":{"observed_at":"2026-08-04T10:13:21.353472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-06T11:05:16.105361Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-04T10:13:21.445450Z","title":"U-Net: Convolutional net- works for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.445450Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:2bb8005c9639414162122005c85b3a51dbf94989d3b48cb76e4a6f48a69efd36","observation_id":"d45156e3-bf83-457e-bcdf-8ec625675598","resolution":{"observed_at":"2026-08-04T10:13:21.445450Z","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":"2026-08-04T10:13:21.519799Z","title":"3D U-Net: Learning dense volumetric segmentation from sparse anno- tation,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.519799Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:01f861c9b624ed272b47f935ce079590648ba494ce6630a3b30f216ab71cc308","observation_id":"57997590-c4db-415e-90a6-0c5d67ec609a","resolution":{"observed_at":"2026-08-04T10:13:21.519799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.09748","last_updated":"2023-03-02T09:06:55Z","snapshot_observed_at":"2026-07-06T14:32:37.317828Z","submitted_at":"2022-12-19T18:59:58Z","title":"Scalable Diffusion Models with Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.09748","snapshot_observed_at":"2026-08-04T10:13:21.666549Z","title":"Scalable diffusion models with transformers,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.666549Z"},"links":{"cited_paper":"/paper/2212.09748","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:40faa7b7f060a3c0fc07fc022ad82224aa841f4b2b5da5b2144602904012626b","observation_id":"e3048279-d3da-4a61-94bb-448a2da79eca","resolution":{"observed_at":"2026-08-04T10:13:21.666549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1506.04214","last_updated":"2015-09-19T11:02:03Z","snapshot_observed_at":"2026-08-07T13:58:38.865727Z","submitted_at":"2015-06-13T03:19:24Z","title":"Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1506.04214","snapshot_observed_at":"2026-08-04T10:13:21.816671Z","title":"Convo- lutional LSTM network: A machine learning approach for precipitation nowcasting,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.816671Z"},"links":{"cited_paper":"/paper/1506.04214","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:6bc6a275c1af456985d067392e038d26009e3fb9ad241ccab0f223dc5f34b6e8","observation_id":"74c3f2d0-68cd-44b6-a2dc-c9e7c596bf0b","resolution":{"observed_at":"2026-08-04T10:13:21.816671Z","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":"2026-08-04T10:13:21.972755Z","title":"Study on channel model for frequencies from 0.5 to 100 GHz,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:21.972755Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:6a59c316eea8f13b882705292f6e3706b639870930501332e28b67e8693b328b","observation_id":"3eca132b-2237-4c1f-9cd1-02b693274c1b","resolution":{"observed_at":"2026-08-04T10:13:21.972755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.02957","last_updated":"2025-03-02T10:59:52Z","snapshot_observed_at":"2026-08-04T02:46:42.503486Z","submitted_at":"2024-03-05T13:25:44Z","title":"On the Asymptotic Mean Square Error Optimality of Diffusion Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.02957","snapshot_observed_at":"2026-08-04T10:13:22.149116Z","title":"On the asymptotic mean square error optimality of diffusion models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:22.149116Z"},"links":{"cited_paper":"/paper/2403.02957","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:a36233b70d575d7329a39d1e87e74a7feb694bfafa2d80c18f3e8444e30c9aaa","observation_id":"45a5325f-a493-4b1a-ac60-2ef91c9607c9","resolution":{"observed_at":"2026-08-04T10:13:22.149116Z","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":"2026-08-04T10:13:22.265891Z","title":"Robust estimation of a location parameter,","venue":null,"work_id":null,"year":1964},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:22.265891Z"},"links":{"citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:4f96db717ee03f8a1070fb55a2bc70e4233340ecd2b3233faa45501f8ab2e0bf","observation_id":"120b0da8-3ab1-4c7f-a527-6d84e77814d9","resolution":{"observed_at":"2026-08-04T10:13:22.265891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09672","last_updated":"2021-02-18T23:44:17Z","snapshot_observed_at":"2026-08-06T00:36:41.660457Z","submitted_at":"2021-02-18T23:44:17Z","title":"Improved Denoising Diffusion Probabilistic Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09672","snapshot_observed_at":"2026-08-04T10:13:22.349862Z","title":"Improved denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:22.349862Z"},"links":{"cited_paper":"/paper/2102.09672","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:fbbbf9df025a9ada3a13e3c3abbadbe309186b448d4e1265a3017c5c8102aafe","observation_id":"5ae2c245-4840-4d7f-a9dd-74fbecc8bef8","resolution":{"observed_at":"2026-08-04T10:13:22.349862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","latest_version":2,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-09T10:36:09.651936Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":41,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":41},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2510.11214."}