{"as_of":"2026-08-08T14:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:923d276d3fd6e40feccb38a261a7eb46c726be17b631a36d74e02a57fc637a0a","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T11:22:41.682159Z","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":"2026-05-19T00:41:56.051676Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.11097","last_updated":"2023-04-28T10:04:17Z","snapshot_observed_at":"2026-07-06T14:54:26.321867Z","submitted_at":"2023-02-22T02:38:25Z","title":"A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.11097","snapshot_observed_at":"2026-08-07T11:22:41.682159Z","title":"A multi-modal neural geometric solver with textual clauses parsed from dia- gram.arXiv preprint arXiv:2302.11097, 2023a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.02690","last_updated":"2025-06-03T09:42:49Z","snapshot_observed_at":"2026-08-07T11:15:50.973031Z","submitted_at":"2025-06-03T09:42:49Z","title":"Towards Geometry Problem Solving in the Large Model Era: A Survey","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:22:41.682159Z"},"links":{"cited_paper":"/paper/2302.11097","citing_paper":"/paper/2506.02690"},"observation_digest":"sha256:cb2519c6997f2bb5fce5b027a87be1fa46b73d718140cda37e1381f5f0cb67db","observation_id":"883bd9c9-8ef6-468d-bce5-508d5b03e528","resolution":{"observed_at":"2026-08-07T11:22:41.682159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.11097","last_updated":"2023-04-28T10:04:17Z","snapshot_observed_at":"2026-07-06T14:54:26.321867Z","submitted_at":"2023-02-22T02:38:25Z","title":"A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram","version":2},"cited_work":{"arxiv_id":"2302.11097","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.11097","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A multi- modal neural geometric solver with textual clauses parsed from diagram","venue":null,"work_id":"2debe77e-200f-49de-a075-b1630fbcc80d","year":2023},"citing_paper":{"arxiv_id":"2508.06226","last_updated":"2026-05-14T12:18:38Z","snapshot_observed_at":"2026-08-02T10:40:08.528122Z","submitted_at":"2025-08-08T11:11:37Z","title":"GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines","version":4},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-19T00:38:43.897231Z"},"links":{"cited_paper":"/paper/2302.11097","citing_paper":"/paper/2508.06226"},"observation_digest":"sha256:384c79003968170272db7c24000fdabcaf1a862cc2aa81085f7099e12d287e07","observation_id":"cef20cfe-2727-4adc-b04f-e19bdd7459fb","resolution":{"observed_at":"2026-05-19T00:41:56.053944Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2302.11097/citation-record","integrity":"/paper/2302.11097/integrity","json":"/paper/2302.11097/citation-record.json","paper":"/paper/2302.11097"},"outbound":[],"paper":{"arxiv_id":"2302.11097","last_updated":"2023-04-28T10:04:17Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T14:54:26.321867Z","submitted_at":"2023-02-22T02:38:25Z","title":"A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram"},"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 2 inbound Pith citation observations for arXiv:2302.11097."}