{"as_of":"2026-08-12T09:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:06eb2e8e126162668055903091627b7e6599b72dff2a35b75a2c363a7c4838a0","coverage":[{"denominator":4,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:27:45.887205Z","state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2507.00041/citation-record","integrity":"/paper/2507.00041/integrity","json":"/paper/2507.00041/citation-record.json","paper":"/paper/2507.00041"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:27:45.970069Z","title":null,"venue":null,"work_id":"8b8ebbf5-09dd-4e87-adee-4e272b73f14d","year":null},"citing_paper":{"arxiv_id":"2507.00041","last_updated":"2025-06-22T22:17:42Z","snapshot_observed_at":"2026-08-06T23:20:38.330263Z","submitted_at":"2025-06-22T22:17:42Z","title":"TalentMine: LLM-Based Extraction and Question-Answering from Multimodal Talent Tables","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:45.877221Z"},"links":{"citing_paper":"/paper/2507.00041"},"observation_digest":"sha256:d5fb7608b37ff617e6583f097395ec0ac049bef3dee723f3f47ead9469ebd4be","observation_id":"42a96035-0db5-46b7-b65d-4c136e39d21c","resolution":{"observed_at":"2026-08-06T23:27:45.975374Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:27:45.955167Z","title":null,"venue":null,"work_id":"87db33db-8444-45a8-98ab-1281c02baa1b","year":null},"citing_paper":{"arxiv_id":"2507.00041","last_updated":"2025-06-22T22:17:42Z","snapshot_observed_at":"2026-08-06T23:20:38.330263Z","submitted_at":"2025-06-22T22:17:42Z","title":"TalentMine: LLM-Based Extraction and Question-Answering from Multimodal Talent Tables","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:45.882062Z"},"links":{"citing_paper":"/paper/2507.00041"},"observation_digest":"sha256:ad8350565ba6044ec1950d1fc2f588fe71ffe06c46a0050ba914500d17535eac","observation_id":"075dda8f-e8ab-4ce9-bd9b-1d7f72fe3dc1","resolution":{"observed_at":"2026-08-06T23:27:45.959562Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:27:45.941076Z","title":"###Response: \"\"\" 17 return prompt 18","venue":null,"work_id":"2133198e-69c9-48e8-8e3e-fcd8cba8205f","year":null},"citing_paper":{"arxiv_id":"2507.00041","last_updated":"2025-06-22T22:17:42Z","snapshot_observed_at":"2026-08-06T23:20:38.330263Z","submitted_at":"2025-06-22T22:17:42Z","title":"TalentMine: LLM-Based Extraction and Question-Answering from Multimodal Talent Tables","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:45.887205Z"},"links":{"citing_paper":"/paper/2507.00041"},"observation_digest":"sha256:f49a09aebf821b9293755922188569ea58bf760630540959e4209fd804992a2e","observation_id":"7ea75ad5-eb44-4895-8a72-6df7fe7cf135","resolution":{"observed_at":"2026-08-06T23:27:45.945388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03145","last_updated":"2024-01-17T06:45:29Z","snapshot_observed_at":"2026-08-05T03:00:06.534042Z","submitted_at":"2024-01-06T07:30:41Z","title":"Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2401.03145","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.03145","snapshot_observed_at":"2026-08-06T23:27:45.922711Z","title":"Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection","venue":"cs.CV","work_id":"c3bcda0f-6d76-4281-b219-648ad4aa5a8e","year":2024},"citing_paper":{"arxiv_id":"2507.00041","last_updated":"2025-06-22T22:17:42Z","snapshot_observed_at":"2026-08-06T23:20:38.330263Z","submitted_at":"2025-06-22T22:17:42Z","title":"TalentMine: LLM-Based Extraction and Question-Answering from Multimodal Talent Tables","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:45.871366Z"},"links":{"cited_paper":"/paper/2401.03145","citing_paper":"/paper/2507.00041"},"observation_digest":"sha256:e24827337f170660bd30d75fb907494110af6bd896b65a22ed86ceabc7e2c8e8","observation_id":"73bc1ec8-870b-4e44-aa45-aaf8142d7270","resolution":{"observed_at":"2026-08-06T23:27:45.929662Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.00041","last_updated":"2025-06-22T22:17:42Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-06T23:20:38.330263Z","submitted_at":"2025-06-22T22:17:42Z","title":"TalentMine: LLM-Based Extraction and Question-Answering from Multimodal Talent Tables"},"reference_resolution":{"displayed":4,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":1},"total_outbound_references":4},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2507.00041."}