{"as_of":"2026-08-08T22:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b3bbd0338ecfaa5a5314a8e2baa94a2668626673c0dd1f0d677cd541f01e911f","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T19:36:04.140466Z","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":"2026-07-02T16:17:09.469638Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":"2409.09359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-07-02T16:17:09.469638Z","title":"Symbolic Regression with a Learned Concept Library","venue":null,"work_id":"2cf3ef95-642c-4b4f-8dc4-4e3b3ae6375d","year":2024},"citing_paper":{"arxiv_id":"2410.17448","last_updated":"2026-04-16T15:22:12Z","snapshot_observed_at":"2026-08-03T00:27:15.111806Z","submitted_at":"2024-10-22T21:50:52Z","title":"In Context Learning and Reasoning for Symbolic Regression with Large Language Models","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-23T18:50:40.378720Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2410.17448"},"observation_digest":"sha256:071cc00dcb3d7b67616358265e59b36b794be582d8c99509ecc6616326cef1c6","observation_id":"a34f1301-19d6-43af-ae08-0fe5ed669e73","resolution":{"observed_at":"2026-05-23T18:53:21.065052Z","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":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-07T19:36:04.140466Z","title":"Symbolic regression with a learned concept library","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10060","last_updated":"2025-02-14T10:26:14Z","snapshot_observed_at":"2026-08-07T21:45:50.999874Z","submitted_at":"2025-02-14T10:26:14Z","title":"DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T19:36:04.140466Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2502.10060"},"observation_digest":"sha256:c9c6f0ad5742856dee8f32030d1624faaec11aa9dc45b47a2ca70ab7b9fa2f34","observation_id":"5035b650-f9ed-48e8-af39-13c5c9385d45","resolution":{"observed_at":"2026-08-07T19:36:04.140466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-06T19:26:34.479148Z","title":"Grayeli, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.05858","last_updated":"2025-07-08T10:37:35Z","snapshot_observed_at":"2026-08-07T01:41:11.016435Z","submitted_at":"2025-07-08T10:37:35Z","title":"$\\mathcal{CP}$-Analyses with Symbolic Regression","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:26:34.479148Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2507.05858"},"observation_digest":"sha256:7f1b79e656d0006109f7b1fd0ff2a8f78d693892b1096f59d1a2d6509184c7e5","observation_id":"4d3a13f0-2a8b-4422-8c52-763d139c9ad4","resolution":{"observed_at":"2026-08-06T19:26:34.479148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-05T18:55:18.925085Z","title":"2024 Symbolic Regression with a Learned Concept Library","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13859","last_updated":"2025-08-19T14:18:16Z","snapshot_observed_at":"2026-08-07T01:49:55.965384Z","submitted_at":"2025-08-19T14:18:16Z","title":"Zobrist Hash-based Duplicate Detection in Symbolic Regression","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T18:55:18.925085Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2508.13859"},"observation_digest":"sha256:f012d802a2cbb3904e14825e80f23a3acd078ca0398e93394b07855acc2811d7","observation_id":"b7ddd1fe-878c-4aee-9a64-d1923ce9ddb9","resolution":{"observed_at":"2026-08-05T18:55:18.925085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-05T13:02:25.661491Z","title":"Symbolic regression with a learned concept library","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.01016","last_updated":"2025-08-31T22:42:58Z","snapshot_observed_at":"2026-08-08T01:56:25.487146Z","submitted_at":"2025-08-31T22:42:58Z","title":"Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction","version":1},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-05T13:02:25.661491Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2509.01016"},"observation_digest":"sha256:d46c46d376d354e057dbdbdb8e0bab1c1cf3850d17010567595114240afd086b","observation_id":"76490900-134b-43c7-a68a-89e6983d81df","resolution":{"observed_at":"2026-08-05T13:02:25.661491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-03T21:50:15.648941Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.13663","last_updated":"2026-06-02T16:19:57Z","snapshot_observed_at":"2026-08-06T00:47:45.850094Z","submitted_at":"2025-11-17T18:16:36Z","title":"SAIL: Sound Abstract Interpreters with LLMs","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T21:50:15.648941Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2511.13663"},"observation_digest":"sha256:35913f5e44280078fa6a179cb8aa4effa974d638a8883c3d59e59f7ed443e452","observation_id":"a4f6dd17-b7d1-4342-866a-7c25d4a72dd2","resolution":{"observed_at":"2026-08-03T21:50:15.648941Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-03T10:42:31.305303Z","title":"Symbolic regression with a learned concept library,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.14288","last_updated":"2026-06-17T10:02:49Z","snapshot_observed_at":"2026-08-03T10:42:22.971791Z","submitted_at":"2026-01-14T09:41:01Z","title":"DeepInflation: an AI agent for research and model discovery of inflation","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-03T10:42:31.305303Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2601.14288"},"observation_digest":"sha256:dffa7e66229b05b3f873a61379d490c415fde79375d698a97743154946286710","observation_id":"f06e3c84-ed8f-4cd5-8765-b39b64eb6e0d","resolution":{"observed_at":"2026-08-03T10:42:31.305303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-03T01:09:51.537157Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.10576","last_updated":"2026-07-27T06:08:51Z","snapshot_observed_at":"2026-08-06T15:59:08.028531Z","submitted_at":"2026-02-11T07:02:23Z","title":"LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T01:09:51.537157Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2602.10576"},"observation_digest":"sha256:bf0f1d3f0c2ee39bac3df28d9bacd085e060991ae7fe5a1457f80d369432fe03","observation_id":"20f3e2d7-4869-4732-b2cb-8f5fd7d9f25f","resolution":{"observed_at":"2026-08-03T01:09:51.537157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":"2409.09359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-07-02T16:17:09.469638Z","title":"Symbolic Regression with a Learned Concept Library","venue":null,"work_id":"2cf3ef95-642c-4b4f-8dc4-4e3b3ae6375d","year":2024},"citing_paper":{"arxiv_id":"2606.07704","last_updated":"2026-06-05T09:18:01Z","snapshot_observed_at":"2026-08-02T08:25:05.777025Z","submitted_at":"2026-06-05T09:18:01Z","title":"FunctionEvolve: Structure-Guided Symbolic Regression with LLMs","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-06-27T22:49:40.344762Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2606.07704"},"observation_digest":"sha256:378dca7aa944f6a803686e6d3258e5ca2268f8094371e260bb317ad821015459","observation_id":"1d8be1d7-6ed3-405c-b8f2-8de118670c28","resolution":{"observed_at":"2026-07-02T16:17:09.471143Z","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":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-01T03:05:32.183834Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25236","last_updated":"2026-07-28T03:23:47Z","snapshot_observed_at":"2026-08-07T21:03:50.260810Z","submitted_at":"2026-07-28T03:23:47Z","title":"VisualPatchWorld: Code World Models as Latent Structured Representations for Planning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T03:05:32.183834Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2607.25236"},"observation_digest":"sha256:a90184807b37b4381d2740fb14df7e8ba7d09b35fe204dbe97b159ebaf263de8","observation_id":"e0ec5307-b2cc-4489-807c-eb280e8b4c46","resolution":{"observed_at":"2026-08-01T03:05:32.183834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-03T04:39:25.719578Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29561","last_updated":"2026-07-31T15:52:07Z","snapshot_observed_at":"2026-08-06T16:00:43.662244Z","submitted_at":"2026-07-31T15:52:07Z","title":"MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T04:39:25.719578Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2607.29561"},"observation_digest":"sha256:0503c28f9ea6d6495142cbb9cea20f8aef35576a8ea692bec4cb6158057d7fa9","observation_id":"d7a2d8ce-399c-488b-8102-c5fd295af99b","resolution":{"observed_at":"2026-08-03T04:39:25.719578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09359","snapshot_observed_at":"2026-08-06T00:42:39.100446Z","title":"Symbolic regression with a learned concept library,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.00934","last_updated":"2026-08-02T02:19:55Z","snapshot_observed_at":"2026-08-06T23:25:13.079313Z","submitted_at":"2026-08-02T02:19:55Z","title":"Unified remnant models for aligned-spin, precessing, and eccentric binary black hole mergers","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T00:42:39.100446Z"},"links":{"cited_paper":"/paper/2409.09359","citing_paper":"/paper/2608.00934"},"observation_digest":"sha256:90dc15a79a1f3b26f809dd0306034ebf9f601e154c16e4c1c0cd39ba09524820","observation_id":"cf745667-8eec-43c8-a0a5-5e1e16ad7b1a","resolution":{"observed_at":"2026-08-06T00:42:39.100446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2409.09359/citation-record","integrity":"/paper/2409.09359/integrity","json":"/paper/2409.09359/citation-record.json","paper":"/paper/2409.09359"},"outbound":[],"paper":{"arxiv_id":"2409.09359","last_updated":"2024-12-10T16:24:48Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T01:26:11.680969Z","submitted_at":"2024-09-14T08:17:30Z","title":"Symbolic Regression with a Learned Concept Library"},"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 12 inbound Pith citation observations for arXiv:2409.09359."}