{"as_of":"2026-08-08T20:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b2c012d5bef82898c6db7cba114c9cdf3bd4ff90f59540990355b01109c43f53","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T05:18:44.215847Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T07:56:32.868540Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.05556","last_updated":"2023-10-26T12:11:02Z","snapshot_observed_at":"2026-07-06T12:46:30.292996Z","submitted_at":"2022-03-10T18:59:21Z","title":"On Embeddings for Numerical Features in Tabular Deep Learning","version":4},"cited_work":{"arxiv_id":"2203.05556","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.05556","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv:2203.05556 [cs]","venue":null,"work_id":"aca0095b-5f97-4db1-a287-a5ed6bad84ee","year":null},"citing_paper":{"arxiv_id":"2605.06047","last_updated":"2026-05-08T20:57:06Z","snapshot_observed_at":"2026-07-06T23:18:36.537416Z","submitted_at":"2026-05-07T11:34:21Z","title":"TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T14:07:51.545351Z"},"links":{"cited_paper":"/paper/2203.05556","citing_paper":"/paper/2605.06047"},"observation_digest":"sha256:e19ff9fd06138a13fe9544fdf3af60bd50bf51492a3a545e786bf2d8f4b6a495","observation_id":"2273d165-37b9-465d-ab2f-4d5ad98d8c4e","resolution":{"observed_at":"2026-05-11T18:46:08.392577Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.05556","last_updated":"2023-10-26T12:11:02Z","snapshot_observed_at":"2026-07-06T12:46:30.292996Z","submitted_at":"2022-03-10T18:59:21Z","title":"On Embeddings for Numerical Features in Tabular Deep Learning","version":4},"cited_work":{"arxiv_id":"2203.05556","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.05556","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv:2203.05556 [cs]","venue":null,"work_id":"aca0095b-5f97-4db1-a287-a5ed6bad84ee","year":null},"citing_paper":{"arxiv_id":"2605.06047","last_updated":"2026-05-08T20:57:06Z","snapshot_observed_at":"2026-07-06T23:18:36.537416Z","submitted_at":"2026-05-07T11:34:21Z","title":"TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-12T01:27:56.674153Z"},"links":{"cited_paper":"/paper/2203.05556","citing_paper":"/paper/2605.06047"},"observation_digest":"sha256:38cede229cfd133380f19e6a91e5957c485d22afc2648b26e3a59db76218ec2d","observation_id":"fe0d6231-5537-4365-888d-243fb7b4b1db","resolution":{"observed_at":"2026-05-12T07:56:32.916830Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.05556","last_updated":"2023-10-26T12:11:02Z","snapshot_observed_at":"2026-07-06T12:46:30.292996Z","submitted_at":"2022-03-10T18:59:21Z","title":"On Embeddings for Numerical Features in Tabular Deep Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.05556","snapshot_observed_at":"2026-08-02T05:18:44.215847Z","title":"In: Advances in Neural Information Processing Systems","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.13413","last_updated":"2026-07-15T03:30:46Z","snapshot_observed_at":"2026-08-07T08:27:43.134547Z","submitted_at":"2026-07-15T03:30:46Z","title":"Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T05:18:44.215847Z"},"links":{"cited_paper":"/paper/2203.05556","citing_paper":"/paper/2607.13413"},"observation_digest":"sha256:a4ffaa0699e43ebb58a051f69988e05c33fc58e4510122d0843555073d06ba9f","observation_id":"83e98b12-f39f-4adc-b558-4e408461a1af","resolution":{"observed_at":"2026-08-02T05:18:44.215847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2203.05556/citation-record","integrity":"/paper/2203.05556/integrity","json":"/paper/2203.05556/citation-record.json","paper":"/paper/2203.05556"},"outbound":[],"paper":{"arxiv_id":"2203.05556","last_updated":"2023-10-26T12:11:02Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T12:46:30.292996Z","submitted_at":"2022-03-10T18:59:21Z","title":"On Embeddings for Numerical Features in Tabular Deep Learning"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.05556."}