{"as_of":"2026-08-09T19:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:62e28f8be6d24c8e60ffaa739c472d60d93e9980f46425db7ec10065f05c5ed5","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":"2026-08-09T06:31:02.800959+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":"2026-08-09T15:43:34.581763Z","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":"2026-08-06T19:53:25.249918Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.04484","last_updated":"2024-06-06T20:12:55Z","snapshot_observed_at":"2026-07-06T18:26:50.515452Z","submitted_at":"2024-06-06T20:12:55Z","title":"Step Out and Seek Around: On Warm-Start Training with Incremental Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04484","snapshot_observed_at":"2026-08-09T15:43:34.581763Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.01342","last_updated":"2025-06-15T08:12:44Z","snapshot_observed_at":"2026-08-09T15:34:29.717047Z","submitted_at":"2025-02-03T13:34:53Z","title":"Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-09T15:43:34.581763Z"},"links":{"cited_paper":"/paper/2406.04484","citing_paper":"/paper/2502.01342"},"observation_digest":"sha256:b5eab7695055fe61c6a8e9785a86994a0977ebcc8a591e534d20229ec72a171f","observation_id":"cf5c8228-353b-44f2-aaf2-d37ce479591b","resolution":{"observed_at":"2026-08-09T15:43:34.581763Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04484","last_updated":"2024-06-06T20:12:55Z","snapshot_observed_at":"2026-07-06T18:26:50.515452Z","submitted_at":"2024-06-06T20:12:55Z","title":"Step Out and Seek Around: On Warm-Start Training with Incremental Data","version":1},"cited_work":{"arxiv_id":"2406.04484","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.04484","snapshot_observed_at":"2026-08-06T19:53:25.249918Z","title":"Step Out and Seek Around: On Warm-Start Training with Incremental Data","venue":"cs.CV","work_id":"db0f0334-ec81-4e4d-941f-71e509f1607b","year":2024},"citing_paper":{"arxiv_id":"2507.04683","last_updated":"2025-07-07T06:02:55Z","snapshot_observed_at":"2026-08-07T08:37:19.278160Z","submitted_at":"2025-07-07T06:02:55Z","title":"Recovering Plasticity of Neural Networks via Soft Weight Rescaling","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:53:23.566366Z"},"links":{"cited_paper":"/paper/2406.04484","citing_paper":"/paper/2507.04683"},"observation_digest":"sha256:58ca05e7f05fe64e0b30815a53c0bfd666dff3e60f2ba4cc4013461fce197011","observation_id":"0a252443-f1b9-4c2b-a098-a7476b4b9bb7","resolution":{"observed_at":"2026-08-06T19:53:25.326746Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.04484/citation-record","integrity":"/paper/2406.04484/integrity","json":"/paper/2406.04484/citation-record.json","paper":"/paper/2406.04484"},"outbound":[],"paper":{"arxiv_id":"2406.04484","last_updated":"2024-06-06T20:12:55Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T18:26:50.515452Z","submitted_at":"2024-06-06T20:12:55Z","title":"Step Out and Seek Around: On Warm-Start Training with Incremental Data"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.04484."}