{"as_of":"2026-08-08T20:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c9f3a29987b7602fcebaa6b81d9115edb7b30d1540b5b67a5fc3175ee9a7b849","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:04:52.312464Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2502.08978/citation-record","integrity":"/paper/2502.08978/integrity","json":"/paper/2502.08978/citation-record.json","paper":"/paper/2502.08978"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:04:52.248085Z","title":"Xgboost: A scalable tree boosting system","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.248085Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:e501ad4e032f2fb92fac9427fb8797b1c23546a4dd3fb1825e555fb5f5b8db6e","observation_id":"580546bf-0c44-44b0-b8f5-d1b79e1d9024","resolution":{"observed_at":"2026-08-07T23:04:52.248085Z","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":"2026-08-07T23:04:52.700897Z","title":"Tab PFN : A transformer that solves small tabular classification problems in a second","venue":null,"work_id":"5f3baeee-b86a-4331-af05-82acf7b71e0f","year":2023},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.253691Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:8e8fe99eb4bbee1bfc0c5921c61e548bab657f493392cafb8f9731ae7ec4e7a9","observation_id":"86d3ab6d-f1c1-4a55-a201-b9fd6d57f7e7","resolution":{"observed_at":"2026-08-07T23:04:52.706396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:04:52.259077Z","title":"u ller, Lennart Purucker, Arjun Krishnakumar, Max K \\","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.259077Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:b8536b0b05b174c421f1e13bfb151ce0c028f8b7bb401e2739cfa69d7bf137ed","observation_id":"7d22f613-2a30-441c-a84d-4188340ab856","resolution":{"observed_at":"2026-08-07T23:04:52.259077Z","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":"2026-08-07T23:04:52.673013Z","title":"bladderbatch: Bladder gene expression data illustrating batch effects","venue":null,"work_id":"e8e2bce2-1f5a-43cc-9355-095b4746deaf","year":2016},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.264273Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:3af9e0157491a401752509d0ca5e61284a9bec280b2394a2fd265a9d503ac6cf","observation_id":"f489ac0e-d314-44a8-9653-2dd4a79fbbe0","resolution":{"observed_at":"2026-08-07T23:04:52.678374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":"status/1726286","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:04:52.599551Z","title":null,"venue":null,"work_id":"b3199bca-b6d5-4b49-9393-270054e0ccc2","year":2022},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.269869Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:e2a7b11b48ae5e4e6da79cfddc98a35a8518f9154d90351233ab35bcef9e416c","observation_id":"c84bac6d-7f40-4707-af65-e1bb09c85784","resolution":{"observed_at":"2026-08-07T23:04:52.607679Z","resolver_source":"raw_fallback","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":"2203.12720","last_updated":"2024-11-11T02:49:50Z","snapshot_observed_at":"2026-08-08T02:12:21.795589Z","submitted_at":"2022-03-23T20:53:55Z","title":"Towards Backwards-Compatible Data with Confounded Domain Adaptation","version":3},"cited_work":{"arxiv_id":"2203.12720","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.12720","snapshot_observed_at":"2026-08-07T23:04:52.506727Z","title":"Towards Backwards-Compatible Data with Confounded Domain Adaptation","venue":"stat.ML","work_id":"84ba7e42-c680-4af4-b100-0ab358416675","year":2022},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.274827Z"},"links":{"cited_paper":"/paper/2203.12720","citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:677128668e74f8a3a18c45897db6d7e7034e00e2bafc7d04d0ec4a6224c7796c","observation_id":"8096f342-cb8c-4db0-8780-47ac414f4239","resolution":{"observed_at":"2026-08-07T23:04:52.512298Z","resolver_source":"local_arxiv","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":"2305.02997","last_updated":"2024-07-15T19:00:47Z","snapshot_observed_at":"2026-07-06T15:23:21.708631Z","submitted_at":"2023-05-04T17:04:41Z","title":"When Do Neural Nets Outperform Boosted Trees on Tabular Data?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.02997","snapshot_observed_at":"2026-08-07T23:04:52.281067Z","title":"When do neural nets outperform boosted trees on tabular data? arXiv preprint arXiv:2305.02997, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.281067Z"},"links":{"cited_paper":"/paper/2305.02997","citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:fda4edaca3f4382c6d09dec3d3a0b23f184536b7eb94281ac750cb242d6ea866","observation_id":"c63cf069-3d4f-4317-a191-31669158584c","resolution":{"observed_at":"2026-08-07T23:04:52.281067Z","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":"2026-08-07T23:04:52.654416Z","title":"Transformers can do bayesian inference","venue":null,"work_id":"ca2b9b7c-4984-44f3-8d88-de395de2f005","year":2022},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.286285Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:a445f6a41a6353f5b892ca5bc254ee816daaa3d6b11ff2f67321e142e39fa871","observation_id":"2bd73500-aa68-4757-84b7-5520e5ff923f","resolution":{"observed_at":"2026-08-07T23:04:52.659941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2305.11097","last_updated":"2023-05-18T16:34:21Z","snapshot_observed_at":"2026-08-05T03:37:32.587185Z","submitted_at":"2023-05-18T16:34:21Z","title":"Statistical Foundations of Prior-Data Fitted Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11097","snapshot_observed_at":"2026-08-07T23:04:52.291114Z","title":"Statistical foundations of prior-data fitted networks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.291114Z"},"links":{"cited_paper":"/paper/2305.11097","citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:053e5a2bb88281ca0bec801fcf92c75dedf0666ee0216ebf147ef0ffa3bdd240","observation_id":"36b481a3-caba-4a15-914a-9a0aec5cbd2c","resolution":{"observed_at":"2026-08-07T23:04:52.291114Z","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":"2026-08-07T23:04:52.296457Z","title":"Causality","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.296457Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:7a76e0964c779ec3a86f3f3f44994cb49c7089edf7816b13b350f51cc66334e1","observation_id":"071e573a-7287-43c4-979e-641738b6dd88","resolution":{"observed_at":"2026-08-07T23:04:52.296457Z","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":"2026-08-07T23:04:52.301131Z","title":"Scikit-learn: Machine learning in python","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.301131Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:2d6d67204b839659e6e17f72a616bdaf1f80ceabbdfd731988db629fcedae5e0","observation_id":"0ca7e3b3-0388-476b-ac1c-7a39f28c24c2","resolution":{"observed_at":"2026-08-07T23:04:52.301131Z","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":"status/1583417","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:04:52.438029Z","title":"I am sorry, but this all sounds too inconsequential imho","venue":null,"work_id":"e4e7d9f6-7230-45a1-8c73-716d7b7799db","year":2022},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.306193Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:1b60ec7ee339c63711911c5004d14c7db1fc0b595bb9cf3c2719999a4d640d16","observation_id":"60b90a2a-ec65-4bc9-91b3-dd089f71a920","resolution":{"observed_at":"2026-08-07T23:04:52.449222Z","resolver_source":"raw_fallback","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:04:52.312464Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T23:04:52.312464Z"},"links":{"citing_paper":"/paper/2502.08978"},"observation_digest":"sha256:38790b0c1e262e9563c3e1bcb723a92d188d2ea9fd3f0a923d72b69b2b2ed1df","observation_id":"264b3271-9a4e-4052-8231-ef67dc85ded4","resolution":{"observed_at":"2026-08-07T23:04:52.312464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.08978","last_updated":"2025-02-13T05:28:29Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T12:18:36.890201Z","submitted_at":"2025-02-13T05:28:29Z","title":"What exactly has TabPFN learned to do?"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":3,"verified_fuzzy":3},"total_outbound_references":13},"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 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2502.08978."}