{"as_of":"2026-08-11T03:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4c7a6309e491a787ea2a73f148a013a6f5ddd3fc0721b12dae88efbab7beee51","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T15:21:23.570687Z","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":"2026-05-25T07:36:55.152927Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.03773","last_updated":"2023-02-07T22:05:55Z","snapshot_observed_at":"2026-08-11T01:12:39.939983Z","submitted_at":"2023-02-07T22:05:55Z","title":"What Matters In The Structured Pruning of Generative Language Models?","version":1},"cited_work":{"arxiv_id":"2302.03773","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.03773","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"What matters in the structured pruning of generative language models? arXiv preprint arXiv:2302.03773","venue":null,"work_id":"4c4b92e8-270f-490b-bb10-1dd94407e21d","year":2023},"citing_paper":{"arxiv_id":"2305.07759","last_updated":"2023-05-24T23:30:43Z","snapshot_observed_at":"2026-08-04T10:35:00.917001Z","submitted_at":"2023-05-12T20:56:48Z","title":"TinyStories: How Small Can Language Models Be and Still Speak Coherent English?","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-25T07:36:55.087443Z"},"links":{"cited_paper":"/paper/2302.03773","citing_paper":"/paper/2305.07759"},"observation_digest":"sha256:0c809ceff40157133b9d6921a8b637df91e4ec8fd7d0211a6253791ae7dcce2a","observation_id":"f9bb6cca-ea5f-462f-b87e-a3b640c22764","resolution":{"observed_at":"2026-05-25T07:36:55.156637Z","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":"2302.03773","last_updated":"2023-02-07T22:05:55Z","snapshot_observed_at":"2026-08-11T01:12:39.939983Z","submitted_at":"2023-02-07T22:05:55Z","title":"What Matters In The Structured Pruning of Generative Language Models?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03773","snapshot_observed_at":"2026-08-10T14:46:38.321953Z","title":"What matters in the structured pruning of generative language models?, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.15014","last_updated":"2025-01-28T20:29:44Z","snapshot_observed_at":"2026-08-11T01:12:50.576066Z","submitted_at":"2025-01-25T01:37:03Z","title":"On Accelerating Edge AI: Optimizing Resource-Constrained Environments","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-10T14:46:38.321953Z"},"links":{"cited_paper":"/paper/2302.03773","citing_paper":"/paper/2501.15014"},"observation_digest":"sha256:837f5485a5c92c58a331c781b5de413a5b484aeac2401c55da5f115653c40664","observation_id":"44967318-9bc6-4813-a3a1-b68448dcf17e","resolution":{"observed_at":"2026-08-10T14:46:38.321953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.03773","last_updated":"2023-02-07T22:05:55Z","snapshot_observed_at":"2026-08-11T01:12:39.939983Z","submitted_at":"2023-02-07T22:05:55Z","title":"What Matters In The Structured Pruning of Generative Language Models?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03773","snapshot_observed_at":"2026-08-10T15:21:23.570687Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16376","last_updated":"2025-05-19T00:48:23Z","snapshot_observed_at":"2026-08-11T02:16:52.400744Z","submitted_at":"2025-01-24T02:50:13Z","title":"SwiftPrune: Hessian-Free Weight Pruning for Large Language Models","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T15:21:23.570687Z"},"links":{"cited_paper":"/paper/2302.03773","citing_paper":"/paper/2501.16376"},"observation_digest":"sha256:823fb7c9651385950cbe6f795ee0d4b1c772c65468a60ca1a0031561bb256e82","observation_id":"f61c9a06-f5c9-452c-b827-fb2832b42f46","resolution":{"observed_at":"2026-08-10T15:21:23.570687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.03773","last_updated":"2023-02-07T22:05:55Z","snapshot_observed_at":"2026-08-11T01:12:39.939983Z","submitted_at":"2023-02-07T22:05:55Z","title":"What Matters In The Structured Pruning of Generative Language Models?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03773","snapshot_observed_at":"2026-08-03T08:45:16.488503Z","title":"What matters in the structured pruning of generative language models? arXiv preprint arXiv:2302.03773,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.16366","last_updated":"2026-05-28T20:33:53Z","snapshot_observed_at":"2026-08-06T05:02:37.173762Z","submitted_at":"2026-01-22T23:35:10Z","title":"Post-Training Neural Network Pruning using Graph Curvature","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T08:45:16.488503Z"},"links":{"cited_paper":"/paper/2302.03773","citing_paper":"/paper/2601.16366"},"observation_digest":"sha256:00fbedb7f10aec39e8ca3d04ef3ca34cb7e098d33997e0fd429346fb7a09e4cc","observation_id":"80007b7f-b52a-4a6f-8321-32203d1285be","resolution":{"observed_at":"2026-08-03T08:45:16.488503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2302.03773/citation-record","integrity":"/paper/2302.03773/integrity","json":"/paper/2302.03773/citation-record.json","paper":"/paper/2302.03773"},"outbound":[],"paper":{"arxiv_id":"2302.03773","last_updated":"2023-02-07T22:05:55Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T01:12:39.939983Z","submitted_at":"2023-02-07T22:05:55Z","title":"What Matters In The Structured Pruning of Generative 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":"2026-08-10T06:31:04.303077+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 4 inbound Pith citation observations for arXiv:2302.03773."}