{"as_of":"2026-08-22T04:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:239fb8e87756b3700bafdd506550457b2231629cf0002da7ab9c792a43776c99","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:16:18.076642Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2506.15688/citation-record","integrity":"/paper/2506.15688/integrity","json":"/paper/2506.15688/citation-record.json","paper":"/paper/2506.15688"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:16:32.440854Z","title":"Cisco annual Internet report (2018–2023) white paper,","venue":null,"work_id":"df24eaeb-548b-4320-9163-4ba479ab2c46","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.296594Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:321342faa3040a3bcbbcea52347ed1ca4db72b16dca450da2b8b60adda2a29a8","observation_id":"b3194d68-f133-4d36-a4d6-1d4e5fb329d6","resolution":{"observed_at":"2026-08-07T14:16:32.510030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:32.265021Z","title":"Mining the situation: Spatiotemporal traffic prediction with big data,","venue":null,"work_id":"a0689ac4-3300-44f2-8357-901c8cf1c1ca","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.346784Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:cf7d00c10eabf2ed82d3c9af240f8588ae0aa2262ce5212d3d04b5e385d250d9","observation_id":"734953fd-6aa7-4079-a779-e8effce1228d","resolution":{"observed_at":"2026-08-07T14:16:32.355964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:32.074522Z","title":"D2D communications-assisted traffic offloading in integrated cellular-WiFi networks,","venue":null,"work_id":"742a9138-6aab-4fba-9444-ff26487c1f28","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.442298Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:f1033435c9daf0ec713defd9f7cc4a7e9910853ac114f96901aff711189c8976","observation_id":"1a62fe59-b270-46ee-aa49-864aecfced95","resolution":{"observed_at":"2026-08-07T14:16:32.136018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:31.911346Z","title":"ITU launches new Focus Group to study machine learning in 5G systems,","venue":null,"work_id":"fd1e5382-1dc0-4cea-98ef-eeff6ba8075b","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.445683Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:5380a2ee77e90cb9e4102c23d51fd578f3d361eb757bc05f1cdb9191b5aa8e67","observation_id":"e14df89b-e2cc-4047-8076-40c9eb2a2e72","resolution":{"observed_at":"2026-08-07T14:16:31.997823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:31.678633Z","title":"Deep network analyzer (dna): A big data analytics platform for cellular networks,","venue":null,"work_id":"98abd790-a609-4008-a1ac-39262a66f1f5","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.449880Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:bc306985f73252c361e635c3a55be939ccd2d540041f8970077c99edfcfa0c9e","observation_id":"3c229b8d-0641-41d8-8d31-40e4bec80172","resolution":{"observed_at":"2026-08-07T14:16:31.838283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:31.470431Z","title":"Active learning for wireless iot intrusion detection,","venue":null,"work_id":"5128af2b-079c-45ed-9964-06b96c4cdeeb","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.532860Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:373920149d8c9e132fdc19c75ad8c216a4f2af1e7723924237b008bfe2e19c1d","observation_id":"f44365c4-c57b-495b-aef8-7740e31e19b7","resolution":{"observed_at":"2026-08-07T14:16:31.559910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:31.236200Z","title":"IoT traffic management and integration in the QoS supported network,","venue":null,"work_id":"4b5145be-f16e-4900-ab57-bd16847ca3e1","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.612355Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:75d3f2a62d561638c91e593d2335e28bf8a2ffe30670660508f04c0a6f02eea1","observation_id":"61e9b2fd-d83f-4b91-a46d-c1d7bf4461c6","resolution":{"observed_at":"2026-08-07T14:16:31.365272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:31.094439Z","title":"Traffic flow prediction with big data: A deep learning approach,","venue":null,"work_id":"b487e2fa-04f6-40b0-a8d3-b4ccad7f8caa","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.706498Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:424c3d094e0a31f427c74df9b56026fcddcfaae8e59235fca057d660b7af446c","observation_id":"5b01d3f2-1655-4dfc-b1e0-e2f59cd551cf","resolution":{"observed_at":"2026-08-07T14:16:31.150118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:30.812340Z","title":"Mobile big data: The fuel for data-driven wireless,","venue":null,"work_id":"fe6d2acc-5ab0-41e3-ac06-4e9376f65a91","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.779724Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:880d09d483a3c9221678f7488481a57be855278dff20e925451a12352afbed95","observation_id":"7516c934-1cbd-43c3-a7b7-4438069b1493","resolution":{"observed_at":"2026-08-07T14:16:30.939395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:30.608166Z","title":"Large-scale mobile traffic analysis: A survey,","venue":null,"work_id":"732ccc6d-700b-43a6-a1cd-9b9c8471ae71","year":2016},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.872740Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:ac5a4d4f239667cfc3660c0733b9710a90486bc7505a4da41d2c283b20301bea","observation_id":"d5ea6a72-f312-46a1-bd6d-96ae75dee7cd","resolution":{"observed_at":"2026-08-07T14:16:30.705120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:30.341836Z","title":"A BiGRU autoencoder remain- ing useful life prediction scheme with attention mechanism and skip connection,","venue":null,"work_id":"77dfa54d-12bf-4c6e-8e72-3578a334ebbc","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:10.982732Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:6aba99cf3608fe50bd19adf7ca10a674fd8a3ec0852eeaa220d69ffde77355da","observation_id":"0149dcff-8b2c-4cec-b06c-de4a6c9102e3","resolution":{"observed_at":"2026-08-07T14:16:30.441798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:30.057042Z","title":"Gated recurrent unit network-based cellular traffic prediction,","venue":null,"work_id":"0122eda4-bcf2-4c7a-a824-6677f10a39f5","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.103256Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:726b17642a1d60ba96e87d5815f5b898104d55a5b877dd2bfcca3724b51269fd","observation_id":"a3aa14b1-7a2a-482a-a417-0f0976c6130e","resolution":{"observed_at":"2026-08-07T14:16:30.194163Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:29.857395Z","title":"Mobile traffic prediction from raw data using LSTM networks,","venue":null,"work_id":"29fbc8ad-bbe8-4bb8-ace2-d28c255997e3","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.201616Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:3abc705689aa67d0098da939cab62805aef659c55a9cff1004803952ed06edc9","observation_id":"92c46e8a-3b97-435d-9ec0-23a91e4db5b4","resolution":{"observed_at":"2026-08-07T14:16:29.967119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:29.672056Z","title":"Pc2a: Predicting collective contextual anomalies via lstm with deep generative model,","venue":null,"work_id":"a9c3ad32-2765-428d-aee2-cdebe4cb0a4c","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.247926Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:81fb9180e9e4f295eb1f13a450e00e62560e7292bb05013e8af828eadc87c142","observation_id":"635c2cd4-7b13-4258-838d-9e9038e70b9a","resolution":{"observed_at":"2026-08-07T14:16:29.798074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:29.404371Z","title":"Time-wise attention aided convolutional neural network for data-driven cellular traffic prediction,","venue":null,"work_id":"c0da568e-4bf1-43d3-bba4-ff7770ad61c1","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.334821Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:1fa7ed5e8726f373d7c82f3aa8aa6e6f8ce9081826f3461c0be058ac0029fcd1","observation_id":"2580ed41-fbd2-49bc-ad38-145ff5abcfb0","resolution":{"observed_at":"2026-08-07T14:16:29.524753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:29.150116Z","title":"Spatiotemporal feature residual propagation for action prediction,","venue":null,"work_id":"7e3f16db-c56a-40c3-b42a-da3581ac50b2","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.427894Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:62aa7131838596f6f1b6f3e6e4b1e02a330b00edb00341f66b7c1fbca5c16f76","observation_id":"611b57a4-b774-4d8d-9226-2cbcce86a5a1","resolution":{"observed_at":"2026-08-07T14:16:29.250835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:28.936646Z","title":"Wireless traffic modeling and prediction using seasonal ARIMA models,","venue":null,"work_id":"65cf7dd0-39ad-42a5-a6e9-89c642c5eaef","year":2005},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.521734Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:3b077bdb9145e8b0d96937cf0abfe666f9c372832ff41ffaa13458465f2085c4","observation_id":"0d8da8e1-9058-48a6-95bc-f223234bf1d2","resolution":{"observed_at":"2026-08-07T14:16:29.034605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:28.751001Z","title":"Traffic prediction for mobile network using Holt-Winter’s exponential smoothing,","venue":null,"work_id":"19344ebb-0f3e-4514-8c94-d1e6d91bb82e","year":2007},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.603600Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:8dbe27926dcfa931d3c3ecff8aac1d36a928458a689a51196816d35784fbebbf","observation_id":"c5f3fb1a-22eb-41ad-9e6b-9d26a137ea7a","resolution":{"observed_at":"2026-08-07T14:16:28.836737Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:28.566040Z","title":"DynaNet: Neural Kalman dynamical model for motion estimation and prediction,","venue":null,"work_id":"1015dbb3-a67c-4f2c-bf79-1f48d35bc5ce","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.705567Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:c7d90ef55e93910910dcec7004686065381ea40e50486d7d4140d1b51438649d","observation_id":"fc7278c2-5086-48c4-b6e3-31cdfb20d0d5","resolution":{"observed_at":"2026-08-07T14:16:28.664987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:11.875102Z","title":"KalmanNet: Neural network aided Kalman filtering for partially known dynamics,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.875102Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:5124778a827491350bb3267851d197aaa99482f7779d88524d7c21b00d6ea5bc","observation_id":"99472bbf-14f7-4681-a8c3-8313290143c5","resolution":{"observed_at":"2026-08-07T14:16:11.875102Z","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":"2026-08-07T14:16:28.414403Z","title":"Deep state space models for time series forecasting,","venue":null,"work_id":"946a8959-6647-4307-a8b4-323486180783","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:11.991293Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:934bd447769636487fb1c0785bf38e50003d97b0c265d5a7a122995a5e8dc247","observation_id":"338324b3-c1cc-49c0-b2c5-5fcfce0f1ff6","resolution":{"observed_at":"2026-08-07T14:16:28.480411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:28.255285Z","title":"Time series prediction using support vector machines: A survey,","venue":null,"work_id":"043d02b4-fae4-48b0-8d1e-2b4d3d55007e","year":2009},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.042565Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:7b2b32d40ef755324053cdb9eeb8f33ec8005d0b2bd9936205e0a55a0a21280b","observation_id":"7d1de2db-d602-4928-b9ae-cc6346e63fbf","resolution":{"observed_at":"2026-08-07T14:16:28.329379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:28.092820Z","title":"Deep learning for network traffic monitoring and analysis (NTMA): A survey,","venue":null,"work_id":"c71b3cbf-ca91-4ce8-9b2c-6a3f8c67c65f","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.130068Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:b06120136b558a8e6ae83462c4c36684145ac1378e7ef2c88552b4e8668321d9","observation_id":"69aafc70-313a-4dc1-9a2c-c660dad158da","resolution":{"observed_at":"2026-08-07T14:16:28.161091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:27.941519Z","title":"Deep learning for intelligent wireless net- works: A comprehensive survey,","venue":null,"work_id":"aa3ae244-32ab-42a9-a2a0-aca1a0acfe70","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.271149Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:30120344403249c828b76dfcf21755fcf454f21a85de7b977cffd1a17245e614","observation_id":"b805a7b1-c574-436b-9d77-135fe76f05ab","resolution":{"observed_at":"2026-08-07T14:16:28.007990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:27.751376Z","title":"Cellular traffic prediction with machine learning: A survey,","venue":null,"work_id":"3886d29b-0a19-4218-a04f-decf6f314afe","year":2022},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.376552Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:16439c9c92833be83114b877d337ff2d5b1eda18838c3134bb1c586fbcaf0988","observation_id":"c2d00c2c-003f-40be-b449-686b3e4f12f0","resolution":{"observed_at":"2026-08-07T14:16:27.856717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:27.573864Z","title":"A dual-stage attention-based recurrent neural network for time series prediction,","venue":null,"work_id":"6b8c98d2-b171-4fb2-8cbc-a3b550160ffe","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.452035Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:8f7cf22479987f1359a39dc26da0d6879d3bd8ff18c29007401df4b4a1562458","observation_id":"15c579fb-5a5f-4eee-9f23-2d4757f8d0ee","resolution":{"observed_at":"2026-08-07T14:16:27.649705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:12.598162Z","title":"Spatio-temporal wireless traffic prediction with recurrent neural network,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.598162Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:02ba112cccaf60ba55eb85cb859f134d06a03ef858c00302e020967b4b53e16a","observation_id":"8028c3d6-d392-41f4-8002-4f04f54ff906","resolution":{"observed_at":"2026-08-07T14:16:12.598162Z","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":"2026-08-07T14:16:27.382817Z","title":"Short-term residential load forecasting based on LSTM recurrent neural network,","venue":null,"work_id":"4eebcad5-0f63-4992-8b0f-ed94c84c97fa","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.708805Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:2ad461adfc161b080773869af412fc360d9d6f6b3d450ea7788b30062b897d9f","observation_id":"21984cac-7a17-454b-8ac2-078802f2064e","resolution":{"observed_at":"2026-08-07T14:16:27.467731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:27.187983Z","title":"A deep learning framework with spatial-temporal attention mechanism for cellular traffic prediction,","venue":null,"work_id":"cc8bb614-821f-4277-9f8b-8ce510f5509e","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:12.915252Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:d4a5e318c3245b62f1630c84497b98b54553e573864c075d9b86789469c9629d","observation_id":"677ac577-c3a5-4011-99e7-15970d1989bf","resolution":{"observed_at":"2026-08-07T14:16:27.294568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:26.970980Z","title":"Cellular traffic load prediction with LSTM and Gaussian process regression,","venue":null,"work_id":"06bb229f-7e79-4ba3-adb0-a1a25cb4f28d","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.064241Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:155c4a565c32ee96708dfd0942ad605e7783bfc9a11fb7942320d3613e2b458e","observation_id":"14987406-9463-466d-9a70-6d09d5217c39","resolution":{"observed_at":"2026-08-07T14:16:27.076115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:26.690781Z","title":"Data-augmentation- based cellular traffic prediction in edge-computing-enabled smart city,","venue":null,"work_id":"e67bbfdc-232a-40e5-8347-30a79a875c44","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.183788Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:b1aff4babcc1c4e1a3ce1c5433c86c6f193f3cdfddded4b3eb1e661b99fbd65d","observation_id":"767c2862-3e23-4a33-9430-653d66a0bdd4","resolution":{"observed_at":"2026-08-07T14:16:26.848990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:26.446620Z","title":"Mobile demand forecasting via deep graph-sequence spatiotemporal modeling in cellular networks,","venue":null,"work_id":"f8e7d265-43e6-48d4-8931-d81554178a69","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.368341Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:7d417fbddee376e0e321282487d0f398a18066b0591d98c29f61ed5b7fd84343","observation_id":"8dee4e23-5279-43bf-b136-fc627ff1be69","resolution":{"observed_at":"2026-08-07T14:16:26.523849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:26.258334Z","title":"Cellular network traffic prediction incorporating handover: A graph convolutional approach,","venue":null,"work_id":"4ede7ec0-5d28-4f6d-888b-2146b96ed074","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.460937Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:03c70248a037e67c87fc480dcef49231b8a64c9f9ea03b874d57e608e10500d4","observation_id":"558d545d-264f-4dcb-aaa0-b45e61a0b1e2","resolution":{"observed_at":"2026-08-07T14:16:26.348224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:26.117455Z","title":"Graph attention spatial- temporal network with collaborative global-local learning for citywide mobile traffic prediction,","venue":null,"work_id":"22ca33b8-3a76-49d1-b3a8-26c63a151b33","year":2022},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.570725Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:405571c29a606a994d7add6d1ce1603b10a5be704c51f693e30153dd9e1937d8","observation_id":"82812f9b-fc58-411a-ac25-df14a2750033","resolution":{"observed_at":"2026-08-07T14:16:26.161760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.985858Z","title":"Graph-based deep learning for communication networks: A survey,","venue":null,"work_id":"f132fe81-7b82-4f80-913a-2d3e9dc6ed70","year":2022},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.647564Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:2a19df662cd51ed452babe7d54163c12b027f43bf4775cd17f3fe91df42a703d","observation_id":"7eb9c5f5-f230-44b1-87ee-a65827e17935","resolution":{"observed_at":"2026-08-07T14:16:26.067831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.813159Z","title":"Network traffic prediction based on diffusion convo- lutional recurrent neural networks,","venue":null,"work_id":"d84c594a-166c-46e1-b34a-abad4db00800","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.736541Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:242a2bda9313d5d2804270576b209167dbde1f1de7d8ce257b3e422b9dd8ad0f","observation_id":"198a7867-caea-4a9e-ba12-441e24ea6f87","resolution":{"observed_at":"2026-08-07T14:16:25.913316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.618389Z","title":"Big data driven mobile traffic understanding and forecasting: A time series approach,","venue":null,"work_id":"2a3090d5-dc3a-47ec-9da1-ebbdb61f871a","year":2016},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.827481Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:edb565253f89f66cc475f6f296949459718aa083922dbc3a24021bf3a4861f2f","observation_id":"86df72a2-205a-45af-812a-18bb0c03b240","resolution":{"observed_at":"2026-08-07T14:16:25.712890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.450230Z","title":"Spatio-temporal analysis and prediction of cellular traffic in metropo- lis,","venue":null,"work_id":"c70a086d-fd7a-4c60-94a5-0290df130cd3","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.918276Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:0400e22da6bf08247ae94ddd3f48a4e65cf1d736994280db0a9d3aa4950444c1","observation_id":"73cbb814-a7b3-498d-b182-dd10f974067c","resolution":{"observed_at":"2026-08-07T14:16:25.516982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.270695Z","title":"Towards accurate prediction for high-dimensional and highly-variable cloud workloads with deep learning,","venue":null,"work_id":"fbe1fd53-ac61-4b68-8763-a8ba326af7a1","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:13.993297Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:1fd64ed03faa1abb7792a67806113d652c7eff2b83ebeac4a6031f975660bfa7","observation_id":"494c3c9f-60af-4dcc-9413-e0c75cc3cb70","resolution":{"observed_at":"2026-08-07T14:16:25.363550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:25.053433Z","title":"Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach,","venue":null,"work_id":"d5f6f6c4-48dd-4d3b-9769-48151a983271","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.067667Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:faa01ee29eda555552208043c8b5e0f6a9315f21a6492da7c8e740bf3d38e0b4","observation_id":"74107065-92e3-47b6-8a6d-d16c1ffdaed8","resolution":{"observed_at":"2026-08-07T14:16:25.162838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:24.771238Z","title":"Citywide cellular traffic prediction based on densely connected convolutional neural networks,","venue":null,"work_id":"6e193173-9760-437d-a41c-f8547bd83e12","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.152652Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:9faebe31380f3c3692305d172a8ca94b2837709dfb44e2bb16820b74e5c17655","observation_id":"fda13479-5252-411f-8668-5ce1d8198f70","resolution":{"observed_at":"2026-08-07T14:16:24.891747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:24.406249Z","title":"DeepRTP: A deep spatio-temporal residual network for regional traffic prediction,","venue":null,"work_id":"6244c6f5-b78d-4232-a550-7ce9bf801529","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.235878Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:b1a8b17a8e8deb24b7c89c953fb3211bfe08be066226eaa3b9981638a1be08e3","observation_id":"cf8b955c-2793-48fc-a763-fa128199e940","resolution":{"observed_at":"2026-08-07T14:16:24.563856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:24.120970Z","title":"A study of deep learning networks on mobile traffic forecasting,","venue":null,"work_id":"88f97d01-9286-4be7-86bb-fdb81c771c7d","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.338794Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:001b45e45e5a386a64beef80dbf2c6e4c7462c0cda004021ef321583eab47ba7","observation_id":"909a43f0-414f-4728-8e34-072f1f66fa2a","resolution":{"observed_at":"2026-08-07T14:16:24.259391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:23.865622Z","title":"Deep irregular convolutional residual LSTM for urban traffic passenger flows prediction,","venue":null,"work_id":"217da384-b63c-495d-9bf0-bd73815e6728","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.504284Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:0d062b257807364cada37232fae427f00bf5e4f76885d8a98878993749d42519","observation_id":"b7c3faf6-0265-45d2-a879-b9cbe1a74bac","resolution":{"observed_at":"2026-08-07T14:16:23.989074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:23.566398Z","title":"Spatial-temporal attention-convolution network for citywide cellular traffic prediction,","venue":null,"work_id":"0bd7a6cf-15db-4c3c-b5f7-67aef2dc5ee4","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.672276Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:27f8e12c71fa35fffe7e4f224cd15171fc24afeda60d0cc4af01d678214a1050","observation_id":"ca819147-e881-46cb-ac32-fa213ec624fb","resolution":{"observed_at":"2026-08-07T14:16:23.740521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:23.299653Z","title":"ST-Tran: Spatial-temporal transformer for cellular traffic prediction,","venue":null,"work_id":"bd28b921-44a4-48d0-bba9-bd0573919586","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.789440Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:6fca010b87cdff3e42567fc695117f874804fee57cc8336850aac44fe32f7534","observation_id":"6495f2c2-ba57-42d3-883e-d954ab847da9","resolution":{"observed_at":"2026-08-07T14:16:23.429470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:22.979785Z","title":"Deep learning for spatio-temporal data mining: A survey,","venue":null,"work_id":"acaf8be0-0ccf-46f8-9211-d57be69ee7ee","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:14.961810Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:51dbb0fdee5f110bb7fc3a9af7c800db249adab33e1a611276afbc700d6f1511","observation_id":"bb522341-925e-4c51-9421-fb71192438d9","resolution":{"observed_at":"2026-08-07T14:16:23.123805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:22.688897Z","title":"DeepTP: An end-to- end neural network for mobile cellular traffic prediction,","venue":null,"work_id":"b1aa50a1-a1b8-4945-b0dc-8bd8e5f99cc2","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.051092Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:cde853c7b83a04f6bb234605dec93a0d7c8b098d9689a0bb9549b04523181da2","observation_id":"b1fee08a-52b8-462d-8971-bbf346fb9eee","resolution":{"observed_at":"2026-08-07T14:16:22.820944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:22.425054Z","title":"ST-DenNetFus: A new deep learning approach for network demand prediction,","venue":null,"work_id":"886b7808-64c8-4fe4-ad41-76b0ac440040","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.202786Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:a7b53947dffb4d406a212e7a01ec69ece673919d121595e75b8e50a8e63d8427","observation_id":"4c4cc0a8-9ae3-48f6-a1c9-8ed77be31c87","resolution":{"observed_at":"2026-08-07T14:16:22.570802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:15.311981Z","title":"Deep transfer learning for intelligent cellular traffic prediction based on cross-domain big data,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.311981Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:bd5301b27b032cfa4cc739b6674370c1f5f5c8055d54c701d2566c2e0809e049","observation_id":"2707668b-bb09-49bb-9e7b-97c54c069c96","resolution":{"observed_at":"2026-08-07T14:16:15.311981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.01553","last_updated":"2019-12-12T03:36:57Z","snapshot_observed_at":"2026-08-16T23:04:37.047651Z","submitted_at":"2019-12-12T03:36:57Z","title":"DeepAuto: A Hierarchical Deep Learning Framework for Real-Time Prediction in Cellular Networks","version":1},"cited_work":{"arxiv_id":"2001.01553","doi":null,"metadata_source":"pith","pith_arxiv_id":"2001.01553","snapshot_observed_at":"2026-08-07T14:16:18.769436Z","title":"DeepAuto: A Hierarchical Deep Learning Framework for Real-Time Prediction in Cellular Networks","venue":"eess.SP","work_id":"99728aef-282f-404b-88cf-5a2aa5095ba6","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.448292Z"},"links":{"cited_paper":"/paper/2001.01553","citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:c3dedc16b2521aed91c937f07b28f985962c6aad6fb51654a9f51cfc66dbd25b","observation_id":"51f26361-9e3c-4056-b41a-81304b9cde22","resolution":{"observed_at":"2026-08-07T14:16:18.841699Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:22.237576Z","title":"From Twitter to traffic predictor: Next-day morning traffic prediction using social media data,","venue":null,"work_id":"76d2458d-c979-4be7-aaf4-a509115cb3fb","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.600237Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:7952fd542e7991e0ad1d56808e07bda8e5b073949a5fd9aac08a79bc1dd32781","observation_id":"8f5a16cd-19f8-49df-8514-2efa9fdbf4dd","resolution":{"observed_at":"2026-08-07T14:16:22.281243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:22.030618Z","title":"Modeling long- and short- term temporal patterns with deep neural networks,","venue":null,"work_id":"199d62ce-8608-43ac-9e1b-2261e074617d","year":2018},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.744956Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:efb3048df8732896558e2bddc6b5dce97d5e0d13d1a4f94183ab548a96ad2685","observation_id":"d38ef536-2dea-4169-bedd-7fa927c692cf","resolution":{"observed_at":"2026-08-07T14:16:22.136258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:21.802620Z","title":"Towards better forecasting by fusing near and distant future visions,","venue":null,"work_id":"1c1cbc91-5155-414e-a8e3-2c7393fcce92","year":2020},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.830671Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:3dda6a4abb2a9a5db702de4b005fea534242b362a9cdbc2976d4016c354f71bb","observation_id":"ed21a052-664d-4d03-9cb5-83a6630d7efa","resolution":{"observed_at":"2026-08-07T14:16:21.895979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:21.536836Z","title":"Attention is all you need,","venue":null,"work_id":"e58d3245-17b6-4e5d-a654-8d6bc079744f","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:15.968646Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:9f882dfd7a289fcc1f396376f8ddf8a97debd5380bf849cb2a7b97c6d3796670","observation_id":"c976d876-48dc-461f-a056-a478ff4136d2","resolution":{"observed_at":"2026-08-07T14:16:21.667962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:21.318095Z","title":"Recurrent Kalman networks: Factorized inference in high-dimensional deep feature spaces,","venue":null,"work_id":"7f730971-c466-4736-93df-0e00cf28a8f7","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.106939Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:ed55637d3461e634effd9b6d4eb518e934ddd72e295c24c9ddbce04acd99b242","observation_id":"91b1247e-6bbe-427e-adff-77a0a49cec96","resolution":{"observed_at":"2026-08-07T14:16:21.419706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:21.107737Z","title":"Long short-term memory Kalman filters: Recurrent neural estimators for pose regularization,","venue":null,"work_id":"c2177f87-ff3c-4e34-ac4e-d5144cc841d3","year":2017},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.266458Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:c6a8e6938eae581f19afefa750689ca6a6d7205dcf72e2b31a2147a505dceb02","observation_id":"0bc1d5d8-edac-44a5-b3b9-510e1015196c","resolution":{"observed_at":"2026-08-07T14:16:21.230529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:20.930458Z","title":"Moving horizon estimation for multirate system with time-varying time-delays,","venue":null,"work_id":"27c32552-ad84-4f20-80ee-f9d5c5d4059d","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.446405Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:9dacc56517ae70cf0388676e2c333473c668065e5f2a6c8671440517f8aee69c","observation_id":"22d3fbf6-d6c5-40ea-b9da-4a6a71e1082f","resolution":{"observed_at":"2026-08-07T14:16:21.027834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:20.709766Z","title":"Kalman filtering in R,","venue":null,"work_id":"9237eefc-9d0e-4496-8524-76ee852d7b8b","year":2011},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.607768Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:dc79b28b58194d061d0d66f82bf951ef25809a0e04480e93c06eb53948a2a5f6","observation_id":"ddf9c13d-9d6b-43a8-b830-df19a2ae587e","resolution":{"observed_at":"2026-08-07T14:16:20.820227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:20.512984Z","title":"Stochastic stability of the discrete-time extended Kalman filter,","venue":null,"work_id":"af9574b2-d636-4c01-ba01-6b78ae586b15","year":1999},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.721008Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:5c4c7bdabd27677435901be704cd1e312793a99222d43199c346bf85c76ff767","observation_id":"89c8eef5-5b3f-4d73-ae76-7085762ce55c","resolution":{"observed_at":"2026-08-07T14:16:20.626821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:20.323773Z","title":"Kalman filters for nonlinear systems and heavy-tailed noise,","venue":null,"work_id":"0412c889-9e2d-4ab3-a620-cef7f3c8b2fe","year":2013},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.832867Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:a17d8a59d982abe29a8634d97d48f2043a9b0f21ce640a4a0810269d4688a5e7","observation_id":"5bbf96b5-8a88-4cb2-abd5-9dfdb00fa257","resolution":{"observed_at":"2026-08-07T14:16:20.397978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:20.119913Z","title":"On iterative unscented Kalman filter using optimization,","venue":null,"work_id":"ed2d8e3b-fc82-403c-944a-cc5857cefcbf","year":2019},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:16.944570Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:91e2fa292e5d0315b8f20a38acb65069eff3cdfc68985933601d693b9597e092","observation_id":"95e226ba-d2b8-4dd3-99bf-5e63a5ddb574","resolution":{"observed_at":"2026-08-07T14:16:20.204942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:19.903318Z","title":"A multi-source dataset of urban life in the city of Milan and the province of Trentino,","venue":null,"work_id":"0b058b75-508a-4942-b95b-d86c646b31ac","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.065666Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:8ba68039087609cdb7901689f4cc0c1993a75f331a0e36697f8e53ce7b2125ff","observation_id":"37a4823d-c2a4-4252-8cc5-9a67404a5f6f","resolution":{"observed_at":"2026-08-07T14:16:20.003472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:17.169544Z","title":"Telecommunications - SMS, Call, Internet - MI,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.169544Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:9dc6f596ac67fc6e425c07cfa14d60489e1c161f69c1aaac4bf26c4cdd98fb47","observation_id":"36be9673-c2cc-4d94-bdd1-9ee0f260e738","resolution":{"observed_at":"2026-08-07T14:16:17.169544Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-07T14:16:17.207971Z","title":"Telecommunications - SMS, Call, Internet - TN,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.207971Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:67683efc6d29a471bc97ffec74fac20ebcc90d0dcd028a40b8e1d08de4bae88c","observation_id":"cb1995a1-10c8-4619-b8f5-227c6db6984c","resolution":{"observed_at":"2026-08-07T14:16:17.207971Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.7910/dvn/9izalb","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Social Pulse - Milano,","venue":"Harvard Dataverse","work_id":"7fe618a6-768d-4e2c-b3f4-39c10200ad7e","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.326860Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:4aaf4c410d17344ed817555a02f0282bce5c779d40d8b6516d38f0806512e738","observation_id":"2155150a-bd76-4fe1-aa92-a8ad3c6d780a","resolution":{"observed_at":"2026-08-07T14:16:18.517006Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:19.704986Z","title":"MilanoToday,","venue":null,"work_id":"3bd78ee4-ccca-4068-a08d-1f7394d12f45","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.435224Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:b6068d0707677f279f722853c68fbe804e371f32d9c0683590739861c20c8ec1","observation_id":"06ec7fd6-8132-475e-b11f-21f77b03cdaa","resolution":{"observed_at":"2026-08-07T14:16:19.783558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.7910/dvn/5h0nui","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Social Pulse - Trentino,","venue":"Harvard Dataverse","work_id":"bd6adc06-bbd0-42c1-bbdd-ac6ce600108f","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.517073Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:9fa5d126d59536949c96895498a869673c50bd021301e2ee1fef7d10200f2c2c","observation_id":"aeeabda8-e6ef-4a37-87fd-5e25ddfaf8f3","resolution":{"observed_at":"2026-08-07T14:16:18.298343Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:19.551574Z","title":"TrentoToday,","venue":null,"work_id":"ac193069-9a2a-48b3-95cd-4873d37316cf","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.623381Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:dd714ee15f5c54727589a263340635eef7707c4c13c213ab917cf566afc1c97e","observation_id":"0cc5b818-7883-4c03-9b8c-d9e9e9e117a6","resolution":{"observed_at":"2026-08-07T14:16:19.607632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:19.363279Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":"3af75e55-1603-4f60-90c4-14f558418f34","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.715524Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:4690ba809261be76ee382b058e8119d46207cf2737b1cb0fcb20fb58129ba000","observation_id":"239d702e-003b-4bb5-942e-ffa71cbc3605","resolution":{"observed_at":"2026-08-07T14:16:19.474580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:19.139175Z","title":"Entry-flipped transformer for inference and prediction of participant behavior,","venue":null,"work_id":"f81082e8-ff61-4f43-9bce-72ca11920d3f","year":2022},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.852606Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:1466c665bf0830a34854ced99586562eed8d7d55b5d986a422e3076c9aee2fc1","observation_id":"1171e998-4c74-4742-a887-d3c834efeb02","resolution":{"observed_at":"2026-08-07T14:16:19.248323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.05122","last_updated":"2021-07-11T19:40:19Z","snapshot_observed_at":"2026-08-21T09:08:22.702190Z","submitted_at":"2021-07-11T19:40:19Z","title":"Interpretable Deep Feature Propagation for Early Action Recognition","version":1},"cited_work":{"arxiv_id":"2107.05122","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.05122","snapshot_observed_at":"2026-08-07T14:16:18.629622Z","title":"Interpretable Deep Feature Propagation for Early Action Recognition","venue":"cs.CV","work_id":"c8ccd870-b2e2-4643-95a1-0acb8af9cb44","year":2021},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:17.971323Z"},"links":{"cited_paper":"/paper/2107.05122","citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:64b46b58632bbf40f199e6818b1ba76f8536e5ad888bc9f931192a662d6ce9d4","observation_id":"c2d8c8fc-03b4-4744-b507-fc44171ebcd1","resolution":{"observed_at":"2026-08-07T14:16:18.702708Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T14:16:18.966130Z","title":"Prior to joining CUHKSZ in 2015, he held research positions at Huawei (USA), Mitsubishi Electric Research Labs (MERL), Boston and Sony, Tokyo, Japan","venue":null,"work_id":"6bb1d3e7-9364-4e04-b8db-6509e7a61723","year":2015},"citing_paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism","version":1},"reference_index":2008,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:18.076642Z"},"links":{"citing_paper":"/paper/2506.15688"},"observation_digest":"sha256:dac7e17d085cafed1207c1c00da85e860a3d63f4bd605de001210380982dfa4b","observation_id":"51bf30d3-7f09-46b7-b643-0cd8a0525460","resolution":{"observed_at":"2026-08-07T14:16:19.047273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.15688","last_updated":"2025-05-26T04:32:15Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T23:04:55.976034Z","submitted_at":"2025-05-26T04:32:15Z","title":"Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":4,"verified_fuzzy":64},"total_outbound_references":73},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2506.15688."}