{"as_of":"2026-08-11T08:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a9b8a97406774f412e94da3ef363c90d8b0483976d7af3c0e2363c39414148c0","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":"2026-08-11T06:34:44.6726+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":"2026-08-07T05:06:37.677879Z","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":"2026-05-10T09:13:30.361593Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.01032","last_updated":"2024-06-03T06:33:51Z","snapshot_observed_at":"2026-08-04T12:12:08.959274Z","submitted_at":"2024-06-03T06:33:51Z","title":"LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01032","snapshot_observed_at":"2026-08-07T05:06:37.677879Z","title":"CoRRabs/2406.01032 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08743","last_updated":"2025-06-10T12:38:24Z","snapshot_observed_at":"2026-08-09T17:08:42.643946Z","submitted_at":"2025-06-10T12:38:24Z","title":"Bridging RDF Knowledge Graphs with Graph Neural Networks for Semantically-Rich Recommender Systems","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:06:37.677879Z"},"links":{"cited_paper":"/paper/2406.01032","citing_paper":"/paper/2506.08743"},"observation_digest":"sha256:e382168a60e89db5bccbf615c51801ca49ffac5cb5aae1a84f48161ec979767d","observation_id":"12a749a3-cb5e-4584-a848-ac9076d2defd","resolution":{"observed_at":"2026-08-07T05:06:37.677879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01032","last_updated":"2024-06-03T06:33:51Z","snapshot_observed_at":"2026-08-04T12:12:08.959274Z","submitted_at":"2024-06-03T06:33:51Z","title":"LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning","version":1},"cited_work":{"arxiv_id":"2406.01032","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.01032","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Llm and gnn are complementary: Distilling llm for multimodal graph learning","venue":null,"work_id":"014eb06a-aba1-4450-b302-b87382415cdd","year":2024},"citing_paper":{"arxiv_id":"2604.15951","last_updated":"2026-04-20T11:32:15Z","snapshot_observed_at":"2026-07-06T23:03:21.422544Z","submitted_at":"2026-04-17T11:12:55Z","title":"Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-10T09:08:48.468564Z"},"links":{"cited_paper":"/paper/2406.01032","citing_paper":"/paper/2604.15951"},"observation_digest":"sha256:e46a86eebde62ad6f9e8afa3b2130806efefdb769dca91526a7b98aef6fdb407","observation_id":"309046ed-1dd8-41dc-9cb0-dbea80088db0","resolution":{"observed_at":"2026-05-10T09:13:30.364764Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.01032/citation-record","integrity":"/paper/2406.01032/integrity","json":"/paper/2406.01032/citation-record.json","paper":"/paper/2406.01032"},"outbound":[],"paper":{"arxiv_id":"2406.01032","last_updated":"2024-06-03T06:33:51Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T12:12:08.959274Z","submitted_at":"2024-06-03T06:33:51Z","title":"LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.01032."}