{"as_of":"2026-08-11T00:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a6f4dfb6e276afc22e16a43efdc4204bb3bc6ad60debf1110f3a0a81124ae2f","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":"2026-08-09T21:24:54.799279Z","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":"2026-05-25T06:40:24.930157Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.18837","last_updated":"2025-02-27T18:49:33Z","snapshot_observed_at":"2026-07-06T19:39:10.669393Z","submitted_at":"2024-10-24T15:22:53Z","title":"High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18837","snapshot_observed_at":"2026-08-09T21:24:54.799279Z","title":"High- dimensional analysis of knowledge distillation: Weak-to-strong generalization and scaling laws","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.19105","last_updated":"2025-02-03T20:44:05Z","snapshot_observed_at":"2026-08-09T21:14:50.311192Z","submitted_at":"2025-01-31T12:57:58Z","title":"Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T21:24:54.799279Z"},"links":{"cited_paper":"/paper/2410.18837","citing_paper":"/paper/2501.19105"},"observation_digest":"sha256:d5885c73562dd0ea82c7a22764ac86043c2643ce99efd65909b1ca7464171a64","observation_id":"23efeb91-8e79-4ecd-824a-d43630ac8bb8","resolution":{"observed_at":"2026-08-09T21:24:54.799279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18837","last_updated":"2025-02-27T18:49:33Z","snapshot_observed_at":"2026-07-06T19:39:10.669393Z","submitted_at":"2024-10-24T15:22:53Z","title":"High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws","version":2},"cited_work":{"arxiv_id":"2410.18837","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.18837","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2410.18837 , year=","venue":null,"work_id":"76e7e4ad-bc6e-493e-aa05-f7cf6b7868c8","year":null},"citing_paper":{"arxiv_id":"2502.05075","last_updated":"2026-04-19T21:23:04Z","snapshot_observed_at":"2026-08-10T13:21:55.925688Z","submitted_at":"2025-02-07T16:46:43Z","title":"Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension","version":6},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-23T03:24:07.851782Z"},"links":{"cited_paper":"/paper/2410.18837","citing_paper":"/paper/2502.05075"},"observation_digest":"sha256:08e681878fa18b140e82e70d84c68d348e4af3274732196fe235400e06ecdfc3","observation_id":"b4957be1-36c0-49af-b7b8-92a1563f0e93","resolution":{"observed_at":"2026-05-23T03:25:20.524195Z","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":"2410.18837","last_updated":"2025-02-27T18:49:33Z","snapshot_observed_at":"2026-07-06T19:39:10.669393Z","submitted_at":"2024-10-24T15:22:53Z","title":"High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws","version":2},"cited_work":{"arxiv_id":"2410.18837","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.18837","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2410.18837 , year=","venue":null,"work_id":"76e7e4ad-bc6e-493e-aa05-f7cf6b7868c8","year":null},"citing_paper":{"arxiv_id":"2605.17767","last_updated":"2026-05-21T20:45:44Z","snapshot_observed_at":"2026-08-04T06:32:13.198687Z","submitted_at":"2026-05-18T02:37:50Z","title":"Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent","version":1},"reference_index":246,"source":"arxiv_source","source_observed_at":"2026-05-20T01:29:14.555216Z"},"links":{"cited_paper":"/paper/2410.18837","citing_paper":"/paper/2605.17767"},"observation_digest":"sha256:87a8a5ead34b3538962595bb37c658d3f3d440bbe9564a243a147a40614bbf23","observation_id":"a1be95b6-6468-427a-a453-1e4c1be5bf1f","resolution":{"observed_at":"2026-05-20T01:32:55.905257Z","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":"2410.18837","last_updated":"2025-02-27T18:49:33Z","snapshot_observed_at":"2026-07-06T19:39:10.669393Z","submitted_at":"2024-10-24T15:22:53Z","title":"High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws","version":2},"cited_work":{"arxiv_id":"2410.18837","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.18837","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2410.18837 , year=","venue":null,"work_id":"76e7e4ad-bc6e-493e-aa05-f7cf6b7868c8","year":null},"citing_paper":{"arxiv_id":"2605.17767","last_updated":"2026-05-21T20:45:44Z","snapshot_observed_at":"2026-08-04T06:32:13.198687Z","submitted_at":"2026-05-18T02:37:50Z","title":"Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent","version":2},"reference_index":246,"source":"arxiv_source","source_observed_at":"2026-05-25T06:39:16.246591Z"},"links":{"cited_paper":"/paper/2410.18837","citing_paper":"/paper/2605.17767"},"observation_digest":"sha256:345eea6b9f9ba94b9d292d8def98142da8c375b4b1cf62207148324389ce855b","observation_id":"8c436c7c-dbf9-46cd-a60a-0351c7938e89","resolution":{"observed_at":"2026-05-25T06:40:24.933596Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2410.18837/citation-record","integrity":"/paper/2410.18837/integrity","json":"/paper/2410.18837/citation-record.json","paper":"/paper/2410.18837"},"outbound":[],"paper":{"arxiv_id":"2410.18837","last_updated":"2025-02-27T18:49:33Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-07-06T19:39:10.669393Z","submitted_at":"2024-10-24T15:22:53Z","title":"High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws"},"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:2410.18837."}