{"as_of":"2026-08-18T19:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:457cd26802bc025e4231036a11a4659950b3583ff5eb7f130e96f51bef6e947e","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":"2026-08-18T06:34:40.430872+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":"2026-08-11T10:39:45.814412Z","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":"2026-05-11T11:21:00.831241Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.04607","last_updated":"2023-10-06T21:55:57Z","snapshot_observed_at":"2026-08-16T14:54:20.430800Z","submitted_at":"2023-10-06T21:55:57Z","title":"A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04607","snapshot_observed_at":"2026-08-11T10:39:45.814412Z","title":"Available: https://arxiv.org/abs/2310.04607","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.16432","last_updated":"2024-12-21T01:37:59Z","snapshot_observed_at":"2026-08-18T03:48:12.557326Z","submitted_at":"2024-12-21T01:37:59Z","title":"DFModel: Design Space Optimization of Large-Scale Systems Exploiting Dataflow Mappings","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-11T10:39:45.814412Z"},"links":{"cited_paper":"/paper/2310.04607","citing_paper":"/paper/2412.16432"},"observation_digest":"sha256:f7cf7d27a351a84202734ee1a3abe30ced1a63a348b64482469d1c212647f9ed","observation_id":"702d494f-3dfa-4c87-aaef-c07b89db59d6","resolution":{"observed_at":"2026-08-11T10:39:45.814412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04607","last_updated":"2023-10-06T21:55:57Z","snapshot_observed_at":"2026-08-16T14:54:20.430800Z","submitted_at":"2023-10-06T21:55:57Z","title":"A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators","version":1},"cited_work":{"arxiv_id":"2310.04607","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.04607","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Available: https://arxiv.org/abs/2310.04607","venue":null,"work_id":"19dcd42a-eee5-4663-9c49-e6aa88708a6b","year":null},"citing_paper":{"arxiv_id":"2604.10852","last_updated":"2026-04-12T23:10:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-12T23:10:14Z","title":"The xPU-athalon: Quantifying the Competition of AI Acceleration","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T15:01:31.205772Z"},"links":{"cited_paper":"/paper/2310.04607","citing_paper":"/paper/2604.10852"},"observation_digest":"sha256:b8d355385be27d6ee87dfdc3de083037a7a94c3bc6423a51960c21acc3e3a0de","observation_id":"4599f9b4-9c95-42d6-8083-a137619ae18e","resolution":{"observed_at":"2026-05-11T11:21:00.836217Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.04607/citation-record","integrity":"/paper/2310.04607/integrity","json":"/paper/2310.04607/citation-record.json","paper":"/paper/2310.04607"},"outbound":[],"paper":{"arxiv_id":"2310.04607","last_updated":"2023-10-06T21:55:57Z","latest_version":1,"primary_category":"cs.PF","snapshot_observed_at":"2026-08-16T14:54:20.430800Z","submitted_at":"2023-10-06T21:55:57Z","title":"A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.04607."}