{"as_of":"2026-08-09T13:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4ae298506fac863efc4798e6331df0ea5a29a551430b2c11fbd45e667e5d7880","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":"2026-08-09T06:31:02.800959+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":"2026-08-07T05:14:57.273950Z","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":"2026-07-01T22:06:16.794372Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.17787","last_updated":"2025-07-15T17:21:32Z","snapshot_observed_at":"2026-08-06T19:37:15.185342Z","submitted_at":"2024-10-23T11:37:20Z","title":"Large Language Models Engineer Too Many Simple Features For Tabular Data","version":2},"cited_work":{"arxiv_id":"2410.17787","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.17787","snapshot_observed_at":"2026-07-01T22:06:16.794372Z","title":"Large language models engineer too many simple features for tabular data","venue":null,"work_id":"e940a743-9981-4caa-ac43-155944eba109","year":2024},"citing_paper":{"arxiv_id":"2503.14434","last_updated":"2026-05-10T22:59:47Z","snapshot_observed_at":"2026-07-06T20:54:50.337775Z","submitted_at":"2025-03-18T17:11:24Z","title":"LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-22T23:37:02.348595Z"},"links":{"cited_paper":"/paper/2410.17787","citing_paper":"/paper/2503.14434"},"observation_digest":"sha256:99f0e24afa0e3873a42b11bd83fd8f6747a19fd2c6f5dec25ad14e57c6dd4c67","observation_id":"dd451fcd-9cff-4859-81de-e6bb427da70b","resolution":{"observed_at":"2026-05-22T23:37:15.449535Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17787","last_updated":"2025-07-15T17:21:32Z","snapshot_observed_at":"2026-08-06T19:37:15.185342Z","submitted_at":"2024-10-23T11:37:20Z","title":"Large Language Models Engineer Too Many Simple Features For Tabular Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17787","snapshot_observed_at":"2026-08-07T05:14:57.273950Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09085","last_updated":"2025-06-10T08:10:16Z","snapshot_observed_at":"2026-08-09T05:50:10.011776Z","submitted_at":"2025-06-10T08:10:16Z","title":"LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T05:14:57.273950Z"},"links":{"cited_paper":"/paper/2410.17787","citing_paper":"/paper/2506.09085"},"observation_digest":"sha256:242aaedb35891bf7204ada43169081c7ebba048cf22aa16510308f3e7bca3a81","observation_id":"2c509e3b-0669-437d-8e29-4d67c2ed2c93","resolution":{"observed_at":"2026-08-07T05:14:57.273950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17787","last_updated":"2025-07-15T17:21:32Z","snapshot_observed_at":"2026-08-06T19:37:15.185342Z","submitted_at":"2024-10-23T11:37:20Z","title":"Large Language Models Engineer Too Many Simple Features For Tabular Data","version":2},"cited_work":{"arxiv_id":"2410.17787","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.17787","snapshot_observed_at":"2026-07-01T22:06:16.794372Z","title":"Large language models engineer too many simple features for tabular data","venue":null,"work_id":"e940a743-9981-4caa-ac43-155944eba109","year":2024},"citing_paper":{"arxiv_id":"2606.02384","last_updated":"2026-06-01T15:33:43Z","snapshot_observed_at":"2026-07-06T23:42:49.173711Z","submitted_at":"2026-06-01T15:33:43Z","title":"TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-06-28T15:43:46.621365Z"},"links":{"cited_paper":"/paper/2410.17787","citing_paper":"/paper/2606.02384"},"observation_digest":"sha256:ead1c88a9e2b6d67944e7deadc4fd203d62c6b91453141a2eebb6fe598d25e4b","observation_id":"08693777-4843-42e2-a359-856740e6586d","resolution":{"observed_at":"2026-07-01T22:06:16.795910Z","resolver_source":"arxiv_id","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/2410.17787/citation-record","integrity":"/paper/2410.17787/integrity","json":"/paper/2410.17787/citation-record.json","paper":"/paper/2410.17787"},"outbound":[],"paper":{"arxiv_id":"2410.17787","last_updated":"2025-07-15T17:21:32Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T19:37:15.185342Z","submitted_at":"2024-10-23T11:37:20Z","title":"Large Language Models Engineer Too Many Simple Features For Tabular Data"},"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 3 inbound Pith citation observations for arXiv:2410.17787."}