{"as_of":"2026-08-24T04:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:375c83feaf3b61da110dc54cbff03b989bfdaf5fa5eed3041fc1298c8246d9dd","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T07:24:27.255815Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2502.14709","last_updated":"2025-06-20T04:30:04Z","snapshot_observed_at":"2026-08-20T14:41:35.684717Z","submitted_at":"2025-02-20T16:34:46Z","title":"Group-Level Data Selection for Efficient Pretraining","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.14709","snapshot_observed_at":"2026-07-14T07:24:27.255815Z","title":"Group- level data selection for efficient pretraining.arXiv preprint arXiv:2502.14709,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11052","last_updated":"2026-07-13T03:31:03Z","snapshot_observed_at":"2026-08-16T13:35:47.434677Z","submitted_at":"2026-07-13T03:31:03Z","title":"Domain-Aware Scaling Laws Uncover Data Synergy","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-14T07:24:27.255815Z"},"links":{"cited_paper":"/paper/2502.14709","citing_paper":"/paper/2607.11052"},"observation_digest":"sha256:1c04fd9c020c853ad2511f495e7ce583eaf7fb27be1a37457379be4d33808c6e","observation_id":"eacf1bf9-76e9-4370-ae30-206522d7ba0c","resolution":{"observed_at":"2026-07-14T07:24:27.255815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.14709/citation-record","integrity":"/paper/2502.14709/integrity","json":"/paper/2502.14709/citation-record.json","paper":"/paper/2502.14709"},"outbound":[],"paper":{"arxiv_id":"2502.14709","last_updated":"2025-06-20T04:30:04Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-20T14:41:35.684717Z","submitted_at":"2025-02-20T16:34:46Z","title":"Group-Level Data Selection for Efficient Pretraining"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2502.14709."}