{"as_of":"2026-08-14T07:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aca4d2381ce1ffa22bf824d0d5527e04d0be4a5471203e8b89254f22b99c17f1","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":"2026-08-14T06:32:32.682623+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":"2026-08-12T17:40:57.938139Z","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":"2026-08-12T17:40:58.505101Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.07640","last_updated":"2025-01-02T13:46:53Z","snapshot_observed_at":"2026-08-13T00:09:01.489208Z","submitted_at":"2024-05-13T11:00:25Z","title":"Hyperparameter Importance Analysis for Multi-Objective AutoML","version":3},"cited_work":{"arxiv_id":"2405.07640","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.07640","snapshot_observed_at":"2026-08-12T17:40:58.505101Z","title":"Hyperparameter Importance Analysis for Multi-Objective AutoML","venue":"cs.LG","work_id":"07056ce8-1d42-4194-a0cc-b0dfd20c459d","year":2024},"citing_paper":{"arxiv_id":"2411.15191","last_updated":"2025-05-16T11:50:36Z","snapshot_observed_at":"2026-08-12T17:34:45.874217Z","submitted_at":"2024-11-19T09:17:13Z","title":"Finding One's Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T17:40:57.938139Z"},"links":{"cited_paper":"/paper/2405.07640","citing_paper":"/paper/2411.15191"},"observation_digest":"sha256:550788cb09aa1ad07b8fc4ee57bdc0eab41b0f9f2758a563ae8fd0484d49c8c7","observation_id":"27b953ac-948e-430c-ade8-04cc7ee27aca","resolution":{"observed_at":"2026-08-12T17:40:58.512040Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07640","last_updated":"2025-01-02T13:46:53Z","snapshot_observed_at":"2026-08-13T00:09:01.489208Z","submitted_at":"2024-05-13T11:00:25Z","title":"Hyperparameter Importance Analysis for Multi-Objective AutoML","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07640","snapshot_observed_at":"2026-08-01T22:07:29.669963Z","title":"Hyperparame- ter Importance Analysis for Multi-Objective AutoML,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.15884","last_updated":"2026-07-17T11:58:35Z","snapshot_observed_at":"2026-08-06T09:58:05.787141Z","submitted_at":"2026-07-17T11:58:35Z","title":"Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T22:07:29.669963Z"},"links":{"cited_paper":"/paper/2405.07640","citing_paper":"/paper/2607.15884"},"observation_digest":"sha256:b2a06fb571fd701eb554c386dc5d96f856e0cf2f3e9fd5ce2aae57cdb500aef7","observation_id":"8b786afb-ebb0-42f9-bcd0-c7c627279a2e","resolution":{"observed_at":"2026-08-01T22:07:29.669963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2405.07640/citation-record","integrity":"/paper/2405.07640/integrity","json":"/paper/2405.07640/citation-record.json","paper":"/paper/2405.07640"},"outbound":[],"paper":{"arxiv_id":"2405.07640","last_updated":"2025-01-02T13:46:53Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T00:09:01.489208Z","submitted_at":"2024-05-13T11:00:25Z","title":"Hyperparameter Importance Analysis for Multi-Objective AutoML"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.07640."}