{"as_of":"2026-08-19T23:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9fa613a6fcfa85302a771bb549b56d5f01829ddf78203475f77ee938af119821","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":"2026-08-19T06:32:44.657259+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":"2026-08-16T04:15:57.088468Z","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":"2026-08-16T04:15:57.387818Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.01384","last_updated":"2024-05-06T02:29:14Z","snapshot_observed_at":"2026-08-16T14:13:24.801036Z","submitted_at":"2024-03-03T03:27:07Z","title":"On the Compressibility of Quantized Large Language Models","version":2},"cited_work":{"arxiv_id":"2403.01384","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.01384","snapshot_observed_at":"2026-08-16T04:15:57.387818Z","title":"On the Compressibility of Quantized Large Language Models","venue":"cs.LG","work_id":"5d67f15e-4428-4094-9151-870e03908d02","year":2024},"citing_paper":{"arxiv_id":"2505.01742","last_updated":"2025-05-14T13:02:05Z","snapshot_observed_at":"2026-08-19T21:45:56.511824Z","submitted_at":"2025-05-03T08:39:19Z","title":"Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T04:15:57.088468Z"},"links":{"cited_paper":"/paper/2403.01384","citing_paper":"/paper/2505.01742"},"observation_digest":"sha256:bb423c6b14c7cf5cb9c7705b5096100fda189a33671268417a791412b77d0d1b","observation_id":"d608c726-5fa2-4e44-ab13-61a82e034995","resolution":{"observed_at":"2026-08-16T04:15:57.400419Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2403.01384/citation-record","integrity":"/paper/2403.01384/integrity","json":"/paper/2403.01384/citation-record.json","paper":"/paper/2403.01384"},"outbound":[],"paper":{"arxiv_id":"2403.01384","last_updated":"2024-05-06T02:29:14Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T14:13:24.801036Z","submitted_at":"2024-03-03T03:27:07Z","title":"On the Compressibility of Quantized Large Language Models"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2403.01384."}