{"as_of":"2026-08-17T16:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1c4d588b3282bf72bda489716acdc9cbdb18f80ba056f275f1397d35a92a9efc","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":"2026-08-17T06:30:58.91139+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":"2026-08-16T11:13:53.509845Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":6,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.07549","last_updated":"2022-06-03T17:43:39Z","snapshot_observed_at":"2026-08-16T17:21:06.938302Z","submitted_at":"2022-02-15T16:33:48Z","title":"Robust Multi-Objective Bayesian Optimization Under Input Noise","version":4},"cited_work":{"arxiv_id":"2202.07549","doi":"10.48550/arxiv.2202.07549","metadata_source":"arxiv_reference","pith_arxiv_id":"2202.07549","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Daulton, S","venue":"arXiv (Cornell University)","work_id":"46560303-2376-491a-854d-5edb7fd0e24d","year":2022},"citing_paper":{"arxiv_id":"2504.03943","last_updated":"2025-10-15T16:42:43Z","snapshot_observed_at":"2026-07-30T08:46:55.703258Z","submitted_at":"2025-04-04T21:20:11Z","title":"Multi-Variable Batch Bayesian Optimization in Materials Research: Synthetic Data Analysis of Noise Sensitivity and Problem Landscape Effects","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-22T20:58:32.436749Z"},"links":{"cited_paper":"/paper/2202.07549","citing_paper":"/paper/2504.03943"},"observation_digest":"sha256:c768e46730a1cc10fe5fdedd3b158089f00cac72c0dac79780e586ec4becefef","observation_id":"b0cf586f-6b8f-4e16-b4f3-0fcf3b61bf53","resolution":{"observed_at":"2026-05-22T21:02:07.761712Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07549","last_updated":"2022-06-03T17:43:39Z","snapshot_observed_at":"2026-08-16T17:21:06.938302Z","submitted_at":"2022-02-15T16:33:48Z","title":"Robust Multi-Objective Bayesian Optimization Under Input Noise","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.07549","snapshot_observed_at":"2026-08-16T11:13:53.509845Z","title":"Osborne, Enlu Zhou, and Eytan Bakshy","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.16272","last_updated":"2025-04-22T21:09:33Z","snapshot_observed_at":"2026-08-16T17:39:00.881138Z","submitted_at":"2025-04-22T21:09:33Z","title":"Learning Explainable Dense Reward Shapes via Bayesian Optimization","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-16T11:13:53.509845Z"},"links":{"cited_paper":"/paper/2202.07549","citing_paper":"/paper/2504.16272"},"observation_digest":"sha256:162fbd44b22ae031e3fa98950fa3bd3f31966425488cf618e160bf62ba0eadc8","observation_id":"fdae8e29-b113-42f9-8ed7-9feef875c404","resolution":{"observed_at":"2026-08-16T11:13:53.509845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07549","last_updated":"2022-06-03T17:43:39Z","snapshot_observed_at":"2026-08-16T17:21:06.938302Z","submitted_at":"2022-02-15T16:33:48Z","title":"Robust Multi-Objective Bayesian Optimization Under Input Noise","version":4},"cited_work":{"arxiv_id":"2202.07549","doi":"10.48550/arxiv.2202.07549","metadata_source":"arxiv_reference","pith_arxiv_id":"2202.07549","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Daulton, S","venue":"arXiv (Cornell University)","work_id":"46560303-2376-491a-854d-5edb7fd0e24d","year":2022},"citing_paper":{"arxiv_id":"2604.01328","last_updated":"2026-04-07T15:06:34Z","snapshot_observed_at":"2026-08-12T16:29:49.014588Z","submitted_at":"2026-04-01T19:14:34Z","title":"Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-13T22:06:48.152555Z"},"links":{"cited_paper":"/paper/2202.07549","citing_paper":"/paper/2604.01328"},"observation_digest":"sha256:c259467ea178b2d1c0dc81dd9736cd3140f100335d2c215760c428280ecf2a98","observation_id":"df928731-74bd-408a-9f3b-959f45248a89","resolution":{"observed_at":"2026-05-13T22:08:20.269080Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2202.07549/citation-record","integrity":"/paper/2202.07549/integrity","json":"/paper/2202.07549/citation-record.json","paper":"/paper/2202.07549"},"outbound":[],"paper":{"arxiv_id":"2202.07549","last_updated":"2022-06-03T17:43:39Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T17:21:06.938302Z","submitted_at":"2022-02-15T16:33:48Z","title":"Robust Multi-Objective Bayesian Optimization Under Input Noise"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2202.07549."}