{"as_of":"2026-08-08T20:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:44ce67c95600ff3da25d44f05377750e341189c690b20e7f94a01699b1048094","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":"2026-08-05T18:30:11.258980Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T12:03:54.154854Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.12706","last_updated":"2024-11-20T09:35:09Z","snapshot_observed_at":"2026-08-05T08:45:30.045156Z","submitted_at":"2024-05-21T11:54:16Z","title":"Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12706","snapshot_observed_at":"2026-08-05T18:30:11.258980Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.14948","last_updated":"2025-08-20T10:18:01Z","snapshot_observed_at":"2026-08-05T18:30:07.186617Z","submitted_at":"2025-08-20T10:18:01Z","title":"Large Foundation Model for Ads Recommendation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T18:30:11.258980Z"},"links":{"cited_paper":"/paper/2405.12706","citing_paper":"/paper/2508.14948"},"observation_digest":"sha256:f5edb4a8286c0d6e0445c00fd7d68fb5a4909ba0b967baf438d4f4e6af772b7f","observation_id":"c97b1154-cd9e-4e39-965f-e6c07e4589e4","resolution":{"observed_at":"2026-08-05T18:30:11.258980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12706","last_updated":"2024-11-20T09:35:09Z","snapshot_observed_at":"2026-08-05T08:45:30.045156Z","submitted_at":"2024-05-21T11:54:16Z","title":"Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation","version":2},"cited_work":{"arxiv_id":"2405.12706","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.12706","snapshot_observed_at":"2026-08-05T12:03:54.154854Z","title":"Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation","venue":"cs.IR","work_id":"27a85934-b768-4a67-ac7d-0bcc4ded4b1a","year":2024},"citing_paper":{"arxiv_id":"2509.02017","last_updated":"2025-09-02T07:02:29Z","snapshot_observed_at":"2026-08-06T21:43:31.105575Z","submitted_at":"2025-09-02T07:02:29Z","title":"Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T12:03:47.785878Z"},"links":{"cited_paper":"/paper/2405.12706","citing_paper":"/paper/2509.02017"},"observation_digest":"sha256:0320163c5867f98405d4f264f91b52bcf1da85617d5c7ee1ba2d4d47b567965a","observation_id":"e302af5b-43a2-48df-86e2-f75aa866a850","resolution":{"observed_at":"2026-08-05T12:03:54.229572Z","resolver_source":"local_arxiv","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/2405.12706/citation-record","integrity":"/paper/2405.12706/integrity","json":"/paper/2405.12706/citation-record.json","paper":"/paper/2405.12706"},"outbound":[],"paper":{"arxiv_id":"2405.12706","last_updated":"2024-11-20T09:35:09Z","latest_version":2,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-05T08:45:30.045156Z","submitted_at":"2024-05-21T11:54:16Z","title":"Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation"},"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:2405.12706."}