{"as_of":"2026-08-07T16:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7162cf71f83fc0c4726d6817cbd7a47295617baf6dc346f35aec7001612809f9","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-23T17:10:06.053994Z","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":"2026-05-23T17:13:14.029827Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.07461","last_updated":"2024-10-09T22:00:19Z","snapshot_observed_at":"2026-08-07T00:29:52.944504Z","submitted_at":"2024-10-09T22:00:19Z","title":"Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning","version":1},"cited_work":{"arxiv_id":"2410.07461","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.07461","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Is C4 dataset optimal for pruning? an investigation of calibration data for LLM pruning","venue":null,"work_id":"17817164-032c-4aa8-968b-2fa0add026c6","year":2024},"citing_paper":{"arxiv_id":"2412.00069","last_updated":"2026-04-18T21:44:35Z","snapshot_observed_at":"2026-07-06T19:59:06.645605Z","submitted_at":"2024-11-26T00:56:18Z","title":"Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-23T17:10:06.053994Z"},"links":{"cited_paper":"/paper/2410.07461","citing_paper":"/paper/2412.00069"},"observation_digest":"sha256:c63017fb2fc69569081f6762602fd1f0e62e947c8d86e7547874d9995fcf30f4","observation_id":"b7b3971b-1360-49f3-8fd6-00c87a768ecf","resolution":{"observed_at":"2026-05-23T17:13:14.033346Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07461","last_updated":"2024-10-09T22:00:19Z","snapshot_observed_at":"2026-08-07T00:29:52.944504Z","submitted_at":"2024-10-09T22:00:19Z","title":"Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning","version":1},"cited_work":{"arxiv_id":"2410.07461","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.07461","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Is C4 dataset optimal for pruning? an investigation of calibration data for LLM pruning","venue":null,"work_id":"17817164-032c-4aa8-968b-2fa0add026c6","year":2024},"citing_paper":{"arxiv_id":"2509.12464","last_updated":"2026-05-02T10:56:37Z","snapshot_observed_at":"2026-07-06T22:30:02.223630Z","submitted_at":"2025-09-15T21:19:13Z","title":"Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-05-18T15:51:20.540625Z"},"links":{"cited_paper":"/paper/2410.07461","citing_paper":"/paper/2509.12464"},"observation_digest":"sha256:da63291f68749c1ae32f713ee5a0d67b972e71f2cc2332efd37180e295ba978b","observation_id":"d183cf41-3dc1-42e7-8892-6e3b2dc352a3","resolution":{"observed_at":"2026-05-18T15:51:33.780470Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07461","last_updated":"2024-10-09T22:00:19Z","snapshot_observed_at":"2026-08-07T00:29:52.944504Z","submitted_at":"2024-10-09T22:00:19Z","title":"Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning","version":1},"cited_work":{"arxiv_id":"2410.07461","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.07461","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Is C4 dataset optimal for pruning? an investigation of calibration data for LLM pruning","venue":null,"work_id":"17817164-032c-4aa8-968b-2fa0add026c6","year":2024},"citing_paper":{"arxiv_id":"2603.16105","last_updated":"2026-05-25T08:42:21Z","snapshot_observed_at":"2026-08-03T02:45:43.103299Z","submitted_at":"2026-03-17T04:12:08Z","title":"Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-15T10:39:12.418304Z"},"links":{"cited_paper":"/paper/2410.07461","citing_paper":"/paper/2603.16105"},"observation_digest":"sha256:e04eb4c75167f190ce64e20ed723cb37b807e0d4809c53817cab2a40083c0adf","observation_id":"59428d1a-2e8a-4a17-8538-2a4e173ef752","resolution":{"observed_at":"2026-05-15T10:39:56.790507Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.07461/citation-record","integrity":"/paper/2410.07461/integrity","json":"/paper/2410.07461/citation-record.json","paper":"/paper/2410.07461"},"outbound":[],"paper":{"arxiv_id":"2410.07461","last_updated":"2024-10-09T22:00:19Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T00:29:52.944504Z","submitted_at":"2024-10-09T22:00:19Z","title":"Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.07461."}