{"as_of":"2026-08-11T01:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2fc61fe8dbf8aedcaad03d05045f62da9bf4315bec79d224fb51d0d2dfb52d9a","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":"2026-08-10T06:31:04.303077+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":"2026-05-22T10:30:01.910920Z","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":"2026-05-22T10:31:25.492414Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.08785","last_updated":"2024-02-13T20:47:17Z","snapshot_observed_at":"2026-08-10T20:20:16.084691Z","submitted_at":"2024-02-13T20:47:17Z","title":"InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment","version":1},"cited_work":{"arxiv_id":"2402.08785","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.08785","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Instructgraph: Boosting large language models via graph-centric instruction tuning and preference alignment","venue":null,"work_id":"25b5c864-93a5-472c-9a95-b090c81c96db","year":2024},"citing_paper":{"arxiv_id":"2603.02938","last_updated":"2026-05-21T07:56:15Z","snapshot_observed_at":"2026-07-06T22:47:41.997192Z","submitted_at":"2026-03-03T12:47:44Z","title":"Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-22T10:30:01.910920Z"},"links":{"cited_paper":"/paper/2402.08785","citing_paper":"/paper/2603.02938"},"observation_digest":"sha256:d69d2f170b0f2850f9c112e5eae24735764c919d30a56d71e7e3a9aaec97e05d","observation_id":"257e5dbe-f3de-4d86-b0b0-388eb0cca38e","resolution":{"observed_at":"2026-05-22T10:31:25.495337Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08785","last_updated":"2024-02-13T20:47:17Z","snapshot_observed_at":"2026-08-10T20:20:16.084691Z","submitted_at":"2024-02-13T20:47:17Z","title":"InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment","version":1},"cited_work":{"arxiv_id":"2402.08785","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.08785","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Instructgraph: Boosting large language models via graph-centric instruction tuning and preference alignment","venue":null,"work_id":"25b5c864-93a5-472c-9a95-b090c81c96db","year":2024},"citing_paper":{"arxiv_id":"2605.03514","last_updated":"2026-05-05T08:50:28Z","snapshot_observed_at":"2026-07-06T23:16:25.301792Z","submitted_at":"2026-05-05T08:50:28Z","title":"Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-07T16:49:54.542437Z"},"links":{"cited_paper":"/paper/2402.08785","citing_paper":"/paper/2605.03514"},"observation_digest":"sha256:6ebc4e1191b613ffb097ff79495f981b521394a2e84b6f4e243b6fb01adf231c","observation_id":"5d4850c7-27ea-4a90-a53d-d94dfebc0356","resolution":{"observed_at":"2026-05-12T11:01:31.290738Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.08785/citation-record","integrity":"/paper/2402.08785/integrity","json":"/paper/2402.08785/citation-record.json","paper":"/paper/2402.08785"},"outbound":[],"paper":{"arxiv_id":"2402.08785","last_updated":"2024-02-13T20:47:17Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-10T20:20:16.084691Z","submitted_at":"2024-02-13T20:47:17Z","title":"InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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:2402.08785."}