{"as_of":"2026-08-09T14:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f5581eb81ba84bb4a7457d16b7f225f8a0f539abbe1c5dd0a3cfc1619a86d9e6","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T11:03:54.172525Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-08T11:22:17.828549Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2105.00105","last_updated":"2021-04-30T22:08:04Z","snapshot_observed_at":"2026-08-04T21:36:19.116973Z","submitted_at":"2021-04-30T22:08:04Z","title":"Tensor Random Projection for Low Memory Dimension Reduction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.00105","snapshot_observed_at":"2026-08-09T11:03:54.172525Z","title":"Tensor random projection for low memory dimension reduction","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02843","last_updated":"2026-07-09T18:33:42Z","snapshot_observed_at":"2026-08-09T10:52:16.573507Z","submitted_at":"2025-02-05T02:58:21Z","title":"On Trimming Tensor-structured Measurements and Efficient Low-rank Tensor Recovery","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T11:03:54.172525Z"},"links":{"cited_paper":"/paper/2105.00105","citing_paper":"/paper/2502.02843"},"observation_digest":"sha256:50bf0c39233a370e8538b0c83df2c637d364f824078c36bea43f32d58b06bf56","observation_id":"703e4dd1-3df3-4b47-8332-d3be3a11d2b4","resolution":{"observed_at":"2026-08-09T11:03:54.172525Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.00105","last_updated":"2021-04-30T22:08:04Z","snapshot_observed_at":"2026-08-04T21:36:19.116973Z","submitted_at":"2021-04-30T22:08:04Z","title":"Tensor Random Projection for Low Memory Dimension Reduction","version":1},"cited_work":{"arxiv_id":"2105.00105","doi":null,"metadata_source":"pith","pith_arxiv_id":"2105.00105","snapshot_observed_at":"2026-08-08T11:22:17.828549Z","title":"Tensor Random Projection for Low Memory Dimension Reduction","venue":"math.NA","work_id":"5d66ff2b-766b-428e-9b49-52cb4a8714f9","year":2021},"citing_paper":{"arxiv_id":"2502.08029","last_updated":"2025-02-13T18:51:33Z","snapshot_observed_at":"2026-08-09T11:45:55.684787Z","submitted_at":"2025-02-12T00:09:18Z","title":"Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T11:22:17.783614Z"},"links":{"cited_paper":"/paper/2105.00105","citing_paper":"/paper/2502.08029"},"observation_digest":"sha256:28886466cb97dc69a3bf5bdd5fd93228d2fa7e3faec63a2b427f0899933be114","observation_id":"e108c7dc-804a-44e2-b35d-7fabfdd73a5d","resolution":{"observed_at":"2026-08-08T11:22:17.834372Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2105.00105/citation-record","integrity":"/paper/2105.00105/integrity","json":"/paper/2105.00105/citation-record.json","paper":"/paper/2105.00105"},"outbound":[],"paper":{"arxiv_id":"2105.00105","last_updated":"2021-04-30T22:08:04Z","latest_version":1,"primary_category":"math.NA","snapshot_observed_at":"2026-08-04T21:36:19.116973Z","submitted_at":"2021-04-30T22:08:04Z","title":"Tensor Random Projection for Low Memory Dimension Reduction"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.00105."}