{"as_of":"2026-08-22T15:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cd9c23c451c2677c26b470599212595de127bc0f027eda8387f11f5d8a3dd94f","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T10:13:34.306047Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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/2411.19493/citation-record","integrity":"/paper/2411.19493/integrity","json":"/paper/2411.19493/citation-record.json","paper":"/paper/2411.19493"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:13:36.748430Z","title":"An approximation method of origin–destination flow traffic from link load counts,","venue":null,"work_id":"fd82efc3-f490-4771-8d8d-af573d239017","year":2011},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.396438Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:2488bcfed91a8d474ef8c50fadf506b4bb8c5417b6ab0f7543de90fe0d15bff6","observation_id":"03ab6e4b-aed8-4997-b941-0465c4f73039","resolution":{"observed_at":"2026-08-12T10:13:36.754406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.737300Z","title":"Internet traffic matrices: A primer,","venue":null,"work_id":"bfab5216-a02f-4b31-aea1-ba0a993c56a3","year":2013},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.481962Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:d59215d5cead4ad129c080273760508f35f6e6d84412a52a9f5ff769ae842126","observation_id":"1b6547e1-154d-4afc-b151-90a5fc6a76a9","resolution":{"observed_at":"2026-08-12T10:13:36.740672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.573347Z","title":"Intelligent traffic matrix estimation using levenberg- marquardt artificial neural network of large scale ip network,","venue":null,"work_id":"7a8afa43-951e-439f-babb-e211ae47f1df","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.563229Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:cf9aa41b1ec6ef69e9971cad19bfa831fed80364d626830ec202ab2cec57308c","observation_id":"c9afe80d-727f-4c23-bafb-b1bf648979e7","resolution":{"observed_at":"2026-08-12T10:13:36.654284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.560724Z","title":"Mining anomalies using traffic feature distributions,","venue":null,"work_id":"9dc7f0b4-d6a6-4db0-b49a-365b3d1ed9a0","year":2005},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.589898Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:3776823aa0b172b62e5cb56972662255cc5c983941dee648dd7cab0d6b991486","observation_id":"4bc63025-7324-49b5-990e-db6ffbdd9d3e","resolution":{"observed_at":"2026-08-12T10:13:36.565807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.547561Z","title":"{LiveMicro}: An edge computing system for collabo- rative telepathology,","venue":null,"work_id":"70bebe82-d49a-4cb0-b5d8-a8a17ddcd67e","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.606449Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:be41ebe437b1b52b69b2391f2963ed12636f1b2d3eafe7f8077fe74a9ebf1cb1","observation_id":"d94b6dbc-7742-4282-b7e7-e53b79dd41ad","resolution":{"observed_at":"2026-08-12T10:13:36.552847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.536866Z","title":"Cisco systems netflow services export version 9,","venue":null,"work_id":"9d4331e9-77de-46e6-a1e7-e8ca3c40686e","year":2004},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.627363Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:cb5377fb1fb7c9594192b43a500025da1bcfb0e72df3277f241c15ee9b9a6f51","observation_id":"1985de92-b00c-49cb-8970-9e67b4942fe6","resolution":{"observed_at":"2026-08-12T10:13:36.540453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.516422Z","title":"Opentm: Traffic matrix estimator for openflow networks,","venue":null,"work_id":"ddd42073-7b7d-4cf9-ba74-40ab9fd13d34","year":null},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.631338Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:e0c360642f78ed7efb93a9a5b9bafcf65d21b6b326d54005ffcb0d0887f52e72","observation_id":"56f1c217-a53c-4e21-904b-203475bd433f","resolution":{"observed_at":"2026-08-12T10:13:36.525196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.429117Z","title":"Network tomography using genetic algorithms,","venue":null,"work_id":"5239246d-a5a9-4340-9c45-c943e747f425","year":2012},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.634877Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:5daaadec01967e4e67f540ac82cb610c0aa9f70a2a327d30800f1870455505b1","observation_id":"359e4cf2-de29-4670-8d1f-5c197b326d7f","resolution":{"observed_at":"2026-08-12T10:13:36.506415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.413505Z","title":"Network monitoring in software-defined networking: A review,","venue":null,"work_id":"067f4b88-4acb-4a24-815c-4cbbf9959f86","year":2018},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.639506Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:fa90f699fd13f482655e02f2bd2ff2dbc62d8fcdf3ee29a345a5c094cf96df99","observation_id":"62912c53-0d48-4963-8eb4-fe005e422f52","resolution":{"observed_at":"2026-08-12T10:13:36.419101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.395057Z","title":"A review of advanced algebraic approaches enabling network tomography for future network infras- tructures,","venue":null,"work_id":"c0f7f0f8-7ae1-4500-843b-f4e4d15e08d6","year":2020},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.644404Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:f3d29a88bd34c974d42cf0a4e9faa6721d7ae780228e4817cae22d8d5d5f3df7","observation_id":"964a6095-d6c4-48a6-9311-47b226d9d04b","resolution":{"observed_at":"2026-08-12T10:13:36.400485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.259695Z","title":"Spatio- temporal tensor completion for imputing missing in- ternet traffic data,","venue":null,"work_id":"84c41772-3219-4da5-875f-71225dca0269","year":2015},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.649231Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:8172bf039bd6dbf883a5ceb55cf6ebda9727103a8ad2b23945280eac841a71ed","observation_id":"5680506f-8edd-4ef4-ba66-38928fdbc38f","resolution":{"observed_at":"2026-08-12T10:13:36.362775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.243456Z","title":"Neural tensor completion for accurate network monitoring,","venue":null,"work_id":"dc001f73-6bc4-4769-8ba9-b2449b54e446","year":2020},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.652961Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:9b9cbb61c52258592295315b92bb5ebf4298a722cbc4f8a31b21d2d5e3445cae","observation_id":"dd261a24-cad2-4ada-8350-2c6646ecbb18","resolution":{"observed_at":"2026-08-12T10:13:36.247206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.223501Z","title":"Deep adversarial tensor completion for accurate network traffic measurement,","venue":null,"work_id":"a5acbfdd-822b-4eb0-90cd-ca0e3f8ae2a5","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.656149Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:0195a85efcd31f62746cf7ca1e063246d03322964bc251176a377acda0bde355","observation_id":"84e6013b-ca2d-480f-81a3-bf4d06824567","resolution":{"observed_at":"2026-08-12T10:13:36.229314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.198658Z","title":"Accurate estimation of large-scale ip traffic matrix,","venue":null,"work_id":"5e2df76c-48ee-4918-b2ca-2b12bbc2d7bb","year":null},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.660253Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:492db30306840aa0fd14eab9520dc0b937080ff1cd2d217cd4967c196b8f80aa","observation_id":"ac4b8cc8-8576-4533-bbd4-c6eb63a2d3ee","resolution":{"observed_at":"2026-08-12T10:13:36.206044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.054935Z","title":"Traffic matrix estimation: A neural network approach with extended input and expectation maximization iteration,","venue":null,"work_id":"a93c9f3b-32c2-4744-8763-7968c51cae88","year":2016},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.742667Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:8c776f298f898c8d2197dc18c2d10d24f35176d62d9583c3f6df963877ab2826","observation_id":"91e30792-0217-4cc3-a430-f50f10eeb9b7","resolution":{"observed_at":"2026-08-12T10:13:36.127920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:33.766730Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.766730Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:8042bbbea7201fe6d22945f350db85a9de72758d5c967d8317d6b827fff47328","observation_id":"bd6fe983-bcaa-45c0-bef8-fe04d15baf5b","resolution":{"observed_at":"2026-08-12T10:13:33.766730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:13:33.784420Z","title":"Deep unsupervised learning using nonequi- librium thermodynamics,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.784420Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:b0b99263adab566678c80310367df518a60f9173337cda6ccf3436b1c27b40ba","observation_id":"7f1391e4-defe-40b5-94f8-2e8abff937d8","resolution":{"observed_at":"2026-08-12T10:13:33.784420Z","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":"2026-08-12T10:13:35.920620Z","title":"Generative modeling by esti- mating gradients of the data distribution,","venue":null,"work_id":"69126c45-6cc5-4670-95d5-557fcacf7fd9","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.791642Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:b53d19388f371ebfa47a95b02b6e1a1fb058a7288387d34ad8928689f7b8dad2","observation_id":"5d7a5fb4-9ada-4eda-9fd2-5dd3e71780b4","resolution":{"observed_at":"2026-08-12T10:13:35.925795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14687","last_updated":"2024-05-20T04:23:45Z","snapshot_observed_at":"2026-08-14T03:13:28.801183Z","submitted_at":"2022-09-29T11:12:27Z","title":"Diffusion Posterior Sampling for General Noisy Inverse Problems","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14687","snapshot_observed_at":"2026-08-12T10:13:33.795473Z","title":"Diffusion posterior sampling for general noisy in- verse problems,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.795473Z"},"links":{"cited_paper":"/paper/2209.14687","citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:5a0b6ad0ee2638bbb8900d00242ec17d98674cea9aabf372442631d582dca4c6","observation_id":"bd1bd6fd-0805-4bdd-ab62-ced0acb6d09c","resolution":{"observed_at":"2026-08-12T10:13:33.795473Z","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":"2026-08-12T10:13:35.905998Z","title":"Pseudoinverse-guided diffusion models for inverse problems,","venue":null,"work_id":"6ede0bee-69bd-4dd0-9a66-813bd14ea136","year":2022},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.799632Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:715743d30c3b888aaad06a0403fd280d20081e7e74fa4a8b3aa0c1f1312e8d81","observation_id":"06d2c744-4fd2-4bda-90db-0e515b780582","resolution":{"observed_at":"2026-08-12T10:13:35.910388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.00490","last_updated":"2022-12-07T13:29:20Z","snapshot_observed_at":"2026-08-19T15:28:44.366291Z","submitted_at":"2022-12-01T13:33:47Z","title":"Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.00490","snapshot_observed_at":"2026-08-12T10:13:33.803263Z","title":"Zero-shot image restoration using denoising diffusion null-space model,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.803263Z"},"links":{"cited_paper":"/paper/2212.00490","citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:254916cbaf6e7be1e69f2baf22ec911d7445e0e448e14ca24add21035be1ed01","observation_id":"c739e1b1-b50f-4813-8041-a04fa328eb4f","resolution":{"observed_at":"2026-08-12T10:13:33.803263Z","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":"2026-08-12T10:13:35.892250Z","title":"Opentm: traffic matrix estimator for openflow networks,","venue":null,"work_id":"56ed6262-295f-44dc-8ca6-ccb476f8f538","year":2010},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.807088Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:99c4fa737d80f095f09db9b22e6df221afd6b5158cdd7c04730310cd50e7d875","observation_id":"eeaa9d39-f5e5-4381-9dda-aca2125b3b64","resolution":{"observed_at":"2026-08-12T10:13:35.897754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.876763Z","title":"A scalable and error-tolerant solution for traffic matrix as- sessment in hybrid ip/sdn networks,","venue":null,"work_id":"496c3182-e9c9-4d0b-98c1-adeae74928ff","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.810871Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:2b02e66aa30a286bb6926a242e39fc68ef3e447df00d12641540c6d694f5a6eb","observation_id":"f8e7e1b3-56e2-4110-b4d4-6a6e4733d12d","resolution":{"observed_at":"2026-08-12T10:13:35.883183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.790278Z","title":"Spatio-temporal compressive sensing and internet traffic matrices,","venue":null,"work_id":"cca1b73d-7ff8-483e-8a4b-5419790918ec","year":2009},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.814052Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:aed390925eb5e083049e17e9c80e95dc1dac45256d7a4edf9340ec6f841e0e66","observation_id":"64bea414-3697-44f1-b4b0-f43ecd1e45fb","resolution":{"observed_at":"2026-08-12T10:13:35.866351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.635415Z","title":"Spatio-temporal compressive sensing and internet traffic matrices (extended version),","venue":null,"work_id":"3eeb0507-8fb2-4365-88fc-ce48909d9a02","year":2011},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.817678Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:f9d2e15c8e2594e7309cbb1c159ccd4c299f98690126f9bae4e8157a715580de","observation_id":"e2a3b41e-d9aa-4e2d-ba04-33c69b6f6c58","resolution":{"observed_at":"2026-08-12T10:13:35.699504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.614768Z","title":"Network tomography: Estimating source- destination traffic intensities from link data,","venue":null,"work_id":"8fe699a0-de85-4271-9433-99a353286a2a","year":1996},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.857468Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:eabfc1907e5c8352b25b7c6f83d67c97c74a3cbdc7e41f8f6b4b477ff62ab89d","observation_id":"235b383b-cb85-40c4-842e-af10ec5649ac","resolution":{"observed_at":"2026-08-12T10:13:35.618991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.604227Z","title":"Fast accurate computation of large-scale ip traffic matri- ces from link loads,","venue":null,"work_id":"5b40fc43-aecb-4292-aa6a-e3f96af116c5","year":2003},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.899020Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:9c4b442b21abfd6a2e34eea3914fd36458299bef97d5460f53755020d2705c40","observation_id":"492250a5-47a8-4522-8ad1-adff7bd3d35b","resolution":{"observed_at":"2026-08-12T10:13:35.608125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.593154Z","title":"Tripartite graph aided tensor completion for sparse network measurement,","venue":null,"work_id":"49e8dd0f-37c5-44a0-b214-9227b8e675c8","year":2022},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.919689Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:7e2ce85f0825cbfcc44a8fe07f6629fe1c0def46f773634318b2e2d9ffdbbc2f","observation_id":"ea63275d-b4b0-4f73-b073-dd1075664fba","resolution":{"observed_at":"2026-08-12T10:13:35.597313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.415150Z","title":"Neutm: A neural network- based framework for traffic matrix prediction in sdn,","venue":null,"work_id":"252d92a9-cf0f-47a1-9a1b-c3f09fedd4a1","year":2018},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.924239Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:c458f461b41dc5f7e8c2ada78a7a50048e0e684009712e2c8082c79f5c6b3c36","observation_id":"4d80a81e-7df5-4756-9458-1e878a35e8a9","resolution":{"observed_at":"2026-08-12T10:13:35.456022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.192529Z","title":"Deep convolutional lstm network-based traffic matrix prediction with partial in- formation,","venue":null,"work_id":"9f707c21-5539-418a-b9ec-98b9f345121d","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.928103Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:f7a3163dfcbfa6d128d4fc82113128fa829ce22398097a04be77c62dce4ffb24","observation_id":"5b10029c-28f4-419f-a82d-587b5c2930a9","resolution":{"observed_at":"2026-08-12T10:13:35.295617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.179995Z","title":"Ai-assisted traffic matrix prediction using ga-enabled deep ensemble learning for hybrid sdn,","venue":null,"work_id":"bb5142e4-7645-487a-8746-bf40de767da8","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.932491Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:cff17d4f5fecf378eee73b223d32bc83ea93cbdac0219f29d4104fcda19bb1df","observation_id":"95769364-2d0b-4db2-961c-bd0459165283","resolution":{"observed_at":"2026-08-12T10:13:35.185124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.167865Z","title":"A new approach for traffic matrix estimation in high load computer networks based on graph embedding and convolutional neural network,","venue":null,"work_id":"8c845bc0-42d6-421e-af4f-91cd9528e61a","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.935419Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:baf7ead487074917854a3e1921c44a8edd67e2c07238d9e8a95034b4ed205027","observation_id":"b75582cf-f5d6-43f8-be09-de8bddffec13","resolution":{"observed_at":"2026-08-12T10:13:35.172099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.142159Z","title":"Completing and predicting internet traffic matrices using adversar- ial autoencoders and hidden markov models,","venue":null,"work_id":"bebc1af1-b8ef-4f94-bf70-668556ef6bd1","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.939080Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:d74e8403e6bcf44317e8eb58f2f6b1d64aa1ddb2dbd466d73e4eb408117556a2","observation_id":"40432055-86b1-4ed2-b2f2-f8840cf66a18","resolution":{"observed_at":"2026-08-12T10:13:35.159154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.015974Z","title":"Future network traffic matrix synthesis and es- timation based on deep generative models,","venue":null,"work_id":"f7dd9012-aa38-4e11-ba59-a7708f4945b9","year":2021},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.943572Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:23fb1bfe651876a4ed71ec09aae5c7f32b5a561d5db8516453d39247d7fb21b5","observation_id":"67004fd8-31a6-4ea2-abbf-a69996c9c863","resolution":{"observed_at":"2026-08-12T10:13:35.056093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:35.002787Z","title":"Learning based methods for traffic matrix estimation from link measurements,","venue":null,"work_id":"ff0b61ae-8dcb-44e9-8b5d-e6d39be2a1c6","year":2021},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.948844Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:ad67a357efcd5950738989146e828b2eb268c3f84d2f51876067e594b8c37f12","observation_id":"f1f9e528-086f-4536-8b03-9997623c41f5","resolution":{"observed_at":"2026-08-12T10:13:35.007300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.990188Z","title":"Traffic matrix estimation based on denoising diffusion proba- bilistic model,","venue":null,"work_id":"3519dd06-1220-406a-8cd1-0255efc51861","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.952304Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:03acdfbde8b7f13a427a40666df1c1fddbccecbf5e241d4bf8869a5b5f6cca1e","observation_id":"03a4b771-bfb6-4fef-b518-fc88861d4c32","resolution":{"observed_at":"2026-08-12T10:13:34.994764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.976791Z","title":"A case study of the accuracy of snmp measurements,","venue":null,"work_id":"510d6872-5885-482c-be3a-715deba59833","year":2010},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.956794Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:262ff3211bb599a5dc89f4b28880adb85f26d6c1ab2ce188d86a66247bceaf40","observation_id":"b594b8f8-8568-4462-9c70-6c05bd588c79","resolution":{"observed_at":"2026-08-12T10:13:34.980932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.934102Z","title":"Improving diffusion models for inverse problems using manifold constraints,","venue":null,"work_id":"92044728-b627-4472-b46f-eb145e9eec13","year":2022},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.981077Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:eeec52e1112757c23ed623b932574b9cdc8a4d814b8422b4384186de7d5d10a8","observation_id":"8228c02b-48c1-4da8-a844-a61a81b99cb2","resolution":{"observed_at":"2026-08-12T10:13:34.966082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.830038Z","title":"Denoising diffusion models for plug-and-play image restoration,","venue":null,"work_id":"4fe39ccd-0f2f-4d40-8d47-ed1fae398978","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.036471Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:d9011fcdd91d6624e988464f742b48b78a48fa2e9bb80ab74f3cb0d499ed55c8","observation_id":"eb5a1575-670d-4c61-98fc-2b0ba276e8a7","resolution":{"observed_at":"2026-08-12T10:13:34.877926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-08-11T15:38:14.931716Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-12T10:13:34.102560Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.102560Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:16538e33509d08bf3d355a275e8ab5ec2939a7a53faa32a98cdea089ba813893","observation_id":"38783924-3ca8-4d83-8fa5-d07025582f9e","resolution":{"observed_at":"2026-08-12T10:13:34.102560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:13:34.108898Z","title":"Tweedie’s formula and selection bias,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.108898Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:9186a0307829b6ac1e03d0864826e3c60bb8531cbd37f58f4bbbedfb7ab3eebf","observation_id":"16901c65-fc86-4fd1-9181-3e26ecf55fa9","resolution":{"observed_at":"2026-08-12T10:13:34.108898Z","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":"2026-08-12T10:13:34.809693Z","title":"Network tomography: Estimating source- destination traffic intensities from link data,","venue":null,"work_id":"ed5af8d4-ac62-4610-81a4-27c536478e47","year":1996},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.112414Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:537098f127f7d267f3321ae125b79c1579791e0254436794fe97708b5b5cfeff","observation_id":"7308d36b-898f-4b3e-a41b-c607068d6c01","resolution":{"observed_at":"2026-08-12T10:13:34.814420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.13456","last_updated":"2021-02-10T18:17:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-11-26T19:39:10Z","title":"Score-Based Generative Modeling through Stochastic Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.13456","snapshot_observed_at":"2026-08-12T10:13:34.116928Z","title":"Score-based generative mod- eling through stochastic differential equations,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.116928Z"},"links":{"cited_paper":"/paper/2011.13456","citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:6ffdd22570f4954019cfcd89f9cab0865b9d3f2c12f41a822cad962e52df5871","observation_id":"f2867f3a-fe61-4e17-8a00-7a3095e56493","resolution":{"observed_at":"2026-08-12T10:13:34.116928Z","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":"2026-08-12T10:13:34.798226Z","title":"Basisdetect: A model-based network event detection framework,","venue":null,"work_id":"2d394141-3fb3-4754-b2c5-38d3a18e9182","year":2010},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.121016Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:3b1c0dd5b3a696e65fcb9864fb077adb7e508ca31a84e7516159c199d3454081","observation_id":"ce967754-b771-4092-9d8b-989371b36fd6","resolution":{"observed_at":"2026-08-12T10:13:34.802238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.767376Z","title":"At- tention is all you need,","venue":null,"work_id":"a3871000-452a-42b7-9f93-8b62c2875f81","year":2017},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.124858Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:3b72dbf2a8560b15dd9d66c49e730f64c14d24afd55d0585cd50216547ce6fee","observation_id":"594c13f0-c79f-4f51-955e-6b7f47430996","resolution":{"observed_at":"2026-08-12T10:13:34.791246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.697404Z","title":null,"venue":null,"work_id":"0555a36a-a5d1-4eb3-a56d-c6dc852c630d","year":2007},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.128520Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:4ac1ef4258cc2f3e07646381cd3291143af4ff99ea3548e602568b9f083965b2","observation_id":"9972ca05-a79f-43d5-9271-f2dcc2fc5fee","resolution":{"observed_at":"2026-08-12T10:13:34.708458Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.684828Z","title":"Finite mixture models,","venue":null,"work_id":"7dd0e7ce-9dc6-4d51-8f50-9192232029f6","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.132122Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:632b28a583be05631caa55ec70999bca84039f564972b61d940a37189b69b6e1","observation_id":"7cc9f6b0-d071-4831-9a8a-4a21087daa4f","resolution":{"observed_at":"2026-08-12T10:13:34.688535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.674149Z","title":"Abilene network topology data and traffic 18 traces,","venue":null,"work_id":"500687bc-8dc4-4e56-88a3-6921317887f2","year":2004},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.161777Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:5f7d43384e4b907f054e7d1936ce242847548414bcda941a95f207e5b1a742bd","observation_id":"9d52e4c4-d93f-4c1d-a5b6-e0f27c0ab590","resolution":{"observed_at":"2026-08-12T10:13:34.678240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.604506Z","title":"Providing public intradomain traffic matrices to the research community,","venue":null,"work_id":"df33d76b-c5d7-4167-ab19-7e1e463a25c4","year":2006},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.197974Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:df2071ef4d6bc1bb417bcaa1a9398c853099b5511ee5994ceda8cc723e299119","observation_id":"66ae6c8e-0222-443f-a301-d644350df0de","resolution":{"observed_at":"2026-08-12T10:13:34.653122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.24963/ijcai.2020/339","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:13:34.380188Z","title":"Neural tensor model for learning multi-aspect factors in recommender systems,","venue":null,"work_id":"198fc849-e1a0-4489-9463-eb8fb56006dd","year":2020},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.240063Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:e3645191beff2a9109bf30993597557da7d5d742cd6add7c290123669b259a68","observation_id":"215ac669-7a38-4766-908d-154d4dfd321f","resolution":{"observed_at":"2026-08-12T10:13:34.398055Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.591469Z","title":"Neural tensor factorization for temporal interaction learning,","venue":null,"work_id":"d0d17f3b-1e2f-493d-b5b3-c4e1c8b6f4cd","year":2019},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.247618Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:161a5c148c71f773e57b51a91e72bf8c6087c8bbb4e09fc64837777ebc74068f","observation_id":"ca26f905-9bb9-4f9d-afb7-187e75d6604d","resolution":{"observed_at":"2026-08-12T10:13:34.595995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.579090Z","title":"Costco: A neural tensor completion model for sparse tensors,","venue":null,"work_id":"e9fc5f14-3067-4e15-ac0b-72ea093f9b98","year":null},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.252171Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:9d20b0710a754ae8ef7dff3f6e50b2efa30c45f930245d2b2f4a0ca3c32cdf0c","observation_id":"1e6fc1ff-a5e3-4b48-a9ae-fa0db543d81d","resolution":{"observed_at":"2026-08-12T10:13:34.583657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.446900Z","title":"Lightnestle: Quick and accurate neural sequential ten- sor completion via meta learning,","venue":null,"work_id":"d952fdd4-0fd1-4d33-b816-28907ce6a69b","year":2023},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.306047Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:84a58193532f9a2870384906b2135ec890a6371d50aec6507cbee5d7c643e8d8","observation_id":"80399f41-0b77-4ec9-b2b2-dc47a4d848c5","resolution":{"observed_at":"2026-08-12T10:13:34.506484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:36.183111Z","title":"Available: https://www.sciencedirect","venue":null,"work_id":"2a665279-6a44-4188-bcbd-fef1770cc4bb","year":null},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:33.699358Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:40f9880a4c9e785ece5d475c6624591fc34264855fecf1375395e76c5de41770","observation_id":"1f92f81e-cf2a-4220-9b16-0ea797e3dbb0","resolution":{"observed_at":"2026-08-12T10:13:36.187756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T10:13:34.559866Z","title":"Available: https://api.semanticscholar","venue":null,"work_id":"380cac4c-f580-42a2-9a93-e906f68c7f28","year":null},"citing_paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-12T10:13:34.255477Z"},"links":{"citing_paper":"/paper/2411.19493"},"observation_digest":"sha256:8b97a93e104e90d8604760fa87373878f8e34be4ccc7e3beaa30885efdce0260","observation_id":"0ff59cbd-f5f7-49e1-96bb-9708b24d12ee","resolution":{"observed_at":"2026-08-12T10:13:34.570494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.19493","last_updated":"2024-11-29T06:20:34Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-19T15:30:17.647340Z","submitted_at":"2024-11-29T06:20:34Z","title":"Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-based Approach"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":46},"total_outbound_references":55},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2411.19493."}