{"as_of":"2026-08-08T15:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b048003d092928789f02f84207f4ebf7510d657b93a8f136d71c12211198b5f9","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":"2026-08-07T13:00:57.842546Z","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":"2026-07-03T23:19:04.259071Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.02191","last_updated":"2025-01-04T05:05:44Z","snapshot_observed_at":"2026-07-06T20:16:27.318761Z","submitted_at":"2025-01-04T05:05:44Z","title":"On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02191","snapshot_observed_at":"2026-08-07T13:00:57.842546Z","title":"On llm-enhanced mixed-type data imputation with high-order message passing.arXiv preprint arXiv:2501.02191, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.22959","last_updated":"2025-05-29T01:02:53Z","snapshot_observed_at":"2026-08-07T12:54:11.901690Z","submitted_at":"2025-05-29T01:02:53Z","title":"LLM-based HSE Compliance Assessment: Benchmark, Performance, and Advancements","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:00:57.842546Z"},"links":{"cited_paper":"/paper/2501.02191","citing_paper":"/paper/2505.22959"},"observation_digest":"sha256:e857367177d68e22d5ac66e199cd3549155c6b02b4b648ab75a0f4097af6ebf9","observation_id":"1446e32c-0515-4460-bc37-03437e26b8d3","resolution":{"observed_at":"2026-08-07T13:00:57.842546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02191","last_updated":"2025-01-04T05:05:44Z","snapshot_observed_at":"2026-07-06T20:16:27.318761Z","submitted_at":"2025-01-04T05:05:44Z","title":"On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing","version":1},"cited_work":{"arxiv_id":"2501.02191","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.02191","snapshot_observed_at":"2026-07-03T23:19:04.259071Z","title":"Available: https://arxiv.org/abs/2501.02191","venue":null,"work_id":"61ea9a9c-fa2a-46cd-96d5-b2e34a52228b","year":null},"citing_paper":{"arxiv_id":"2606.17582","last_updated":"2026-06-16T06:43:46Z","snapshot_observed_at":"2026-08-07T16:07:11.624751Z","submitted_at":"2026-06-16T06:43:46Z","title":"Collaborative Large and Small Language Models for Accurate and Scalable Data Repair","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-26T22:25:39.533017Z"},"links":{"cited_paper":"/paper/2501.02191","citing_paper":"/paper/2606.17582"},"observation_digest":"sha256:9fb40c0880b9fc1a0247695a544e01213c4373bdeb10202acd287f92509ec9bf","observation_id":"3dd34c46-ef17-497e-87e1-a5270f2696b9","resolution":{"observed_at":"2026-07-03T23:19:04.261902Z","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/2501.02191/citation-record","integrity":"/paper/2501.02191/integrity","json":"/paper/2501.02191/citation-record.json","paper":"/paper/2501.02191"},"outbound":[],"paper":{"arxiv_id":"2501.02191","last_updated":"2025-01-04T05:05:44Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T20:16:27.318761Z","submitted_at":"2025-01-04T05:05:44Z","title":"On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing"},"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:2501.02191."}