{"as_of":"2026-08-14T19:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1d481945e848a3b493e954fc0661890ab97d8bb6805fcd764eafd5f5513e1497","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":"2026-08-12T19:10:33.174672Z","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":"2026-08-11T22:14:10.104250Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2110.03173","last_updated":"2022-09-19T04:47:59Z","snapshot_observed_at":"2026-08-14T13:54:06.322223Z","submitted_at":"2021-10-07T03:56:19Z","title":"Multi-objective Optimization by Learning Space Partitions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03173","snapshot_observed_at":"2026-08-12T19:10:33.174672Z","title":"Multi- objective optimization by learning space partitions,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.10990","last_updated":"2024-11-17T07:24:20Z","snapshot_observed_at":"2026-08-13T23:02:37.964756Z","submitted_at":"2024-11-17T07:24:20Z","title":"Timing-driven Approximate Logic Synthesis Based on Double-chase Grey Wolf Optimizer","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T19:10:33.174672Z"},"links":{"cited_paper":"/paper/2110.03173","citing_paper":"/paper/2411.10990"},"observation_digest":"sha256:af46eb069d5f1f835b600957fdec88745cece7d90af1a7bd2189c0837f670dc0","observation_id":"2b9d88b6-cd31-4b67-9600-aae03a3796a8","resolution":{"observed_at":"2026-08-12T19:10:33.174672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03173","last_updated":"2022-09-19T04:47:59Z","snapshot_observed_at":"2026-08-14T13:54:06.322223Z","submitted_at":"2021-10-07T03:56:19Z","title":"Multi-objective Optimization by Learning Space Partitions","version":4},"cited_work":{"arxiv_id":"2110.03173","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.03173","snapshot_observed_at":"2026-08-11T22:14:10.104250Z","title":"Multi-objective Optimization by Learning Space Partitions","venue":"cs.LG","work_id":"314cec8c-f848-447f-83fc-c6c21a374543","year":2021},"citing_paper":{"arxiv_id":"2412.03718","last_updated":"2025-02-20T13:31:09Z","snapshot_observed_at":"2026-08-14T11:04:10.578241Z","submitted_at":"2024-12-04T21:14:18Z","title":"ParetoFlow: Guided Flows in Multi-Objective Optimization","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-11T22:14:09.686029Z"},"links":{"cited_paper":"/paper/2110.03173","citing_paper":"/paper/2412.03718"},"observation_digest":"sha256:d78c3d54c56041a809e153fac7073282bcbcc22738228b87ef22076f0a977930","observation_id":"d788f4ae-27cc-4f07-87c7-257645c99b3b","resolution":{"observed_at":"2026-08-11T22:14:10.154754Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2110.03173/citation-record","integrity":"/paper/2110.03173/integrity","json":"/paper/2110.03173/citation-record.json","paper":"/paper/2110.03173"},"outbound":[],"paper":{"arxiv_id":"2110.03173","last_updated":"2022-09-19T04:47:59Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T13:54:06.322223Z","submitted_at":"2021-10-07T03:56:19Z","title":"Multi-objective Optimization by Learning Space Partitions"},"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:2110.03173."}