{"as_of":"2026-08-08T10:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de8a7ec55ac8523661323f57f96540c0a3f64567337f35c12181b54cc51545bb","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:43:54.117306Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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":"2026-08-01T23:43:17.665357Z","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":"2026-05-11T03:45:55.367372Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"cited_work":{"arxiv_id":"2505.23913","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.23913","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Simplifying","venue":null,"work_id":"f97e22fb-8cc1-4c06-ac54-ec0f80a6c31e","year":null},"citing_paper":{"arxiv_id":"2605.07775","last_updated":"2026-05-08T14:16:32Z","snapshot_observed_at":"2026-08-01T04:00:34.833595Z","submitted_at":"2026-05-08T14:16:32Z","title":"POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles","version":1},"reference_index":106,"source":"arxiv_source","source_observed_at":"2026-05-11T03:41:21.506458Z"},"links":{"cited_paper":"/paper/2505.23913","citing_paper":"/paper/2605.07775"},"observation_digest":"sha256:d12595787212690075d0050902dc85a8edabb3bba9b80b0f3d066f274e1ab87f","observation_id":"5d67bb28-5364-4282-899f-45896db31586","resolution":{"observed_at":"2026-05-11T03:45:55.373691Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.23913","snapshot_observed_at":"2026-08-01T23:43:17.665357Z","title":"Simplifying B ayesian optimization via in-context direct optimum sampling, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.15277","last_updated":"2026-07-16T17:59:31Z","snapshot_observed_at":"2026-08-06T16:50:03.110275Z","submitted_at":"2026-07-16T17:59:31Z","title":"Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models","version":1},"reference_index":126,"source":"arxiv_source","source_observed_at":"2026-08-01T23:43:17.665357Z"},"links":{"cited_paper":"/paper/2505.23913","citing_paper":"/paper/2607.15277"},"observation_digest":"sha256:b800ca179b6cbf9ce323569d566ca86196988c66e63b6199c6643a072cc633c7","observation_id":"da4601c1-ed2f-4a9c-813a-91b3dee35f07","resolution":{"observed_at":"2026-08-01T23:43:17.665357Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.23913/citation-record","integrity":"/paper/2505.23913/integrity","json":"/paper/2505.23913/citation-record.json","paper":"/paper/2505.23913"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.903907Z","title":"Unexpected improvements to expected improvement for Bayesian optimization","venue":null,"work_id":"965f5f1a-1206-4b8b-bdb8-270efb0e7782","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.349871Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:3fd55b1cca050b26c50312bc58fb903ce033861d30ac597aca638ccea4e235fd","observation_id":"ada694e8-9cdb-45f9-a555-41b3a04ac5a5","resolution":{"observed_at":"2026-08-07T12:44:00.130448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.595206Z","title":"Using confidence bounds for exploitation-exploration trade-offs.JMLR, 3(null), 2003","venue":null,"work_id":"90537b82-53a4-4db0-b03f-8d3ba3137119","year":2003},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.405117Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:c919542a1251903b59bcac7ecf7d5a9ef867a15211b97b592e25a99fd29bae89","observation_id":"3c4e6c2e-0764-4a64-9e54-99ca70d03d44","resolution":{"observed_at":"2026-08-07T12:43:59.690031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.439210Z","title":"Botorch: A framework for efficient monte-carlo bayesian optimization","venue":null,"work_id":"ac1a95ef-88f3-482a-8b11-66b3d2d0b3dc","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.482228Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:d339da41b19b357f70dcb43e3ccadb56dc08f3a5fdff102b93d202577a596feb","observation_id":"d61ea6ee-205b-4e10-ad49-e285299b6d31","resolution":{"observed_at":"2026-08-07T12:43:59.521260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.331556Z","title":"Language models are few-shot learners","venue":null,"work_id":"3dbbbc45-d217-4e8e-b033-3246422a52a0","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.536854Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:2b1b85ff8eea2b59c81f365dc3c3a362f24c1537107690426211ff6f06060a5c","observation_id":"5936666e-875a-417e-b2d3-c182cb2f2cc7","resolution":{"observed_at":"2026-08-07T12:43:59.360653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.276168Z","title":"Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu","venue":null,"work_id":"bebad087-1074-4469-805c-46f028dca57a","year":1995},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.667073Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:ee9bf0d5373c7588b1b1526fae752ebc85dd962fbe2eca64ae7e442e337a8a4b","observation_id":"5dd6a2ef-e93f-4fdb-a765-f83d3b2b027e","resolution":{"observed_at":"2026-08-07T12:43:59.291889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.213900Z","title":"Learning phrase representations using RNN encoder–decoder for statistical machine translation","venue":null,"work_id":"887e08d4-4c18-40c8-ba08-7f4ecd54bf65","year":2014},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.784449Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:55cf4bb580ae7af5c14d0d3e1098e2b37a9a6d1e0878eed5ac9eb3ff207f6fdb","observation_id":"75c31aad-2ee5-407c-83ae-2a692ca1f851","resolution":{"observed_at":"2026-08-07T12:43:59.236606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:49.871133Z","title":"Neural spline flows","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.871133Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:aefa78626ce265bdcb3919e2ee465277bd28ee48525866e6ebde7bdfcfc7719c","observation_id":"40c2b21e-5616-4b9a-8682-e18362a7b736","resolution":{"observed_at":"2026-08-07T12:43:49.871133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.127154Z","title":"Auto-sklearn 2.0: Hands-free automl via meta-learning.JMLR, 23(261), 2022","venue":null,"work_id":"78c1a2e4-e0e1-4c53-9e9a-12962b1f1ca2","year":2022},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:49.969836Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:1d3aa7872dd076387af2e67a833b1b752a760d83c7cb85c118c34f9e99deafe6","observation_id":"d0c43c91-be75-418c-91c4-7a66b20fd71d","resolution":{"observed_at":"2026-08-07T12:43:59.166077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:59.056546Z","title":null,"venue":null,"work_id":"7e1018ef-3d1f-4410-ba92-b81cf1f469b1","year":2018},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.078103Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:f94efbbf607d32bd72b5f83249f35a657a1775600568f73b82db9902f15c2fcd","observation_id":"41b46792-a263-44e9-a3b7-75d9fdd03727","resolution":{"observed_at":"2026-08-07T12:43:59.094435Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:50.174808Z","title":"Cambridge University Press, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.174808Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:33c8785ec83d1a86803ca08d0722fb8097f792dedd0e0d26566e9fb06b1d05b5","observation_id":"fc78cd73-99bd-41af-9e63-1035f03bec27","resolution":{"observed_at":"2026-08-07T12:43:50.174808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.954409Z","title":"Springer, 2010","venue":null,"work_id":"0caf9c1c-78f2-43a5-a88f-6bd09852f42b","year":2010},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.350202Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:1069080d86e9cba53cd78444bd632590600528dc1f2a5e531ea854992139fedd","observation_id":"d708791c-e788-457b-97cb-f9cdd6aea17d","resolution":{"observed_at":"2026-08-07T12:43:58.992867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.877272Z","title":"Text-guided molecule generation with diffusion language model.Proceedings of the AAAI Conference on Artificial Intelligence, 38(1), 2024","venue":null,"work_id":"1e967934-979a-4cdb-b87a-f128d65ba886","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.485012Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:efe584f19953b52b203a45ce9ecec5dbb73c2c8b3faebb5517463de4c70beaba","observation_id":"6d5e9b62-ccc5-42f9-a0d7-c3ceaf4b73eb","resolution":{"observed_at":"2026-08-07T12:43:58.913221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.820787Z","title":"From alchemist to ai chemist","venue":null,"work_id":"7c3e139c-6a7d-4ed9-a984-cc240d535475","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.568597Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:dce17002b9112ea8517452f315ad00722c4f8f9f8f2c26925003da78520529b6","observation_id":"ec949d66-28ab-4613-aedf-4558838407d5","resolution":{"observed_at":"2026-08-07T12:43:58.839089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.706228Z","title":"Constrained Bayesian optimization for automatic chemical design using variational autoencoders.Chem","venue":null,"work_id":"539a46ef-4a2e-401d-92aa-fc004195d2d3","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.709314Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:8bd82f6dd283e80d03dab99354433ca8786b102203d59a4558ac489f99d80d90","observation_id":"77b920e4-0a23-437b-a2e3-e8f53f60692f","resolution":{"observed_at":"2026-08-07T12:43:58.775191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.600555Z","title":"Hickman, Loïc M","venue":null,"work_id":"0673267f-27ce-45db-bdaf-e260fffc5a33","year":2021},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.839151Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:9ca75fad5eadcccc3ac164e491a00057c73761377a29d60a134c6d2ac9126a99","observation_id":"8b657fd4-f8d8-422e-b242-288292309cd7","resolution":{"observed_at":"2026-08-07T12:43:58.629429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.435699Z","title":"Hoffman, and Zoubin Ghahramani","venue":null,"work_id":"07436786-7b21-49ac-af1f-94f7772eef94","year":2014},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:50.962539Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:479dfcfa9b8c1177d44100e037258ab6187a302bd27d4d1ac582446136a2c5b4","observation_id":"38797a90-2163-4916-8da9-6ab604ef6c39","resolution":{"observed_at":"2026-08-07T12:43:58.487646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.377468Z","title":"Pyzer-Knapp, and Alán Aspuru-Guzik","venue":null,"work_id":"e71f3f9f-2e83-4ce6-abe6-b71d3ca0e758","year":2017},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.089706Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:002fdf858caeb301e78ff986fa293c981dde73e41cbdfefb57d2c38f8ff3d351","observation_id":"90f84a71-2359-4b63-a852-7baa0531df2e","resolution":{"observed_at":"2026-08-07T12:43:58.408248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.246143Z","title":"BINOCULARS for efficient, nonmyopic sequential experimental design","venue":null,"work_id":"60ea7bba-6b10-4f1a-9002-977076c6ecda","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.211349Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:28641ce0429d744d150efcabeac70bf67e1d4e76e2898fbd0580fd323cc4bd81","observation_id":"63c24826-072f-43d6-b146-9caff2263d68","resolution":{"observed_at":"2026-08-07T12:43:58.321655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:58.077442Z","title":"Jones, Matthias Schonlau, and William J","venue":null,"work_id":"47f208b8-39b9-484f-81e3-fd5935b2f81a","year":1998},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.320718Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:4cbede67cc31296997daceea7d656ee66066b79dff1993db3ead29a930215d7f","observation_id":"6d4491e7-3039-4907-891e-64335904d60d","resolution":{"observed_at":"2026-08-07T12:43:58.154883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.928264Z","title":"Diffusion models for black-box optimization","venue":null,"work_id":"1fec6ef5-9ad3-4f4f-b162-5be84a8f5672","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.458496Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:0c896ce7e76eb1f80e4bcf05d4f0dcf6a5faad0f6158bcf22fe06d70804991e0","observation_id":"3ea17d1f-ce6a-4287-8bf1-62ad0c1244a5","resolution":{"observed_at":"2026-08-07T12:43:57.999353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.719203Z","title":"Promises and pitfalls of the linearized Laplace in Bayesian optimization","venue":null,"work_id":"452f6dd4-36bb-4671-840b-dc8a9ed8e74c","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.582539Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:b857f7637fa843217eea2020aeecb9809ceec24e0a08eb8d8b705a34d7c1954d","observation_id":"f573b281-52b4-493e-afe9-acaa338d57e7","resolution":{"observed_at":"2026-08-07T12:43:57.830203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.606473Z","title":"A sober look at LLMs for material discovery: Are they actually good for Bayesian optimization over molecules? InICML, 2024","venue":null,"work_id":"ba755a4d-b7bc-4020-85a1-2aefd82571d0","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.697744Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:94f86a178e04c821ab1a4639462cb86c912f87412461e8ee33818c06b244dbd1","observation_id":"3d287dab-a3f8-4c66-9cae-d5ca8cd6a2f0","resolution":{"observed_at":"2026-08-07T12:43:57.663579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.522219Z","title":"How useful is intermittent, asynchronous expert feedback for Bayesian optimization? InSixth Symposium on Advances in Approximate Bayesian Inference-Non Archival Track, 2024","venue":null,"work_id":"02318e41-28ba-459d-b08b-826b545179e4","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.806353Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:21c52bc1d38453b3e0080c25812e5ed6d24d3f2d2dde70cb3bd402e1e0ce7947","observation_id":"d043cc32-fb98-4427-8ae2-2a2d40eed24b","resolution":{"observed_at":"2026-08-07T12:43:57.557641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.457361Z","title":"Model inversion networks for model-based optimization","venue":null,"work_id":"74ee94c9-d58a-46cb-a1af-91d3dbd9195d","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:51.966215Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:e4c99e577387245cff11c7781f981a12724162dfba49a877ddea48bffa3e9574","observation_id":"6cc1169c-4f1c-4ab4-a40a-4474b44a29d1","resolution":{"observed_at":"2026-08-07T12:43:57.482607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.305830Z","title":null,"venue":null,"work_id":"adfe4915-2dae-486f-829b-3270827d7381","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.109793Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:afc637e016eca4efa71a46749d6358e639430903396dafb5e1ba76d9111f1733","observation_id":"eaa111eb-1c05-4f47-8762-63d541253100","resolution":{"observed_at":"2026-08-07T12:43:57.395724Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.144020Z","title":"Amortized in-context Bayesian posterior estimation, 2025","venue":null,"work_id":"b50378db-70ad-4334-9783-7b7d7980e78b","year":2025},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.230654Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:85bb43348423e5e4a4b8d8002ef3a7b7600958f2f06ee8ef55c5b11c1bfae571","observation_id":"79fcc852-5950-4c7b-9422-ec1980658679","resolution":{"observed_at":"2026-08-07T12:43:57.223357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:57.029504Z","title":null,"venue":null,"work_id":"46f70c15-502a-42fa-b742-722e78edbb73","year":1974},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.339356Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:4d820669a241e38b1306f2886bc18e393fd6075cd5d87b2f2d038536b5cd91fc","observation_id":"0e382aae-a6c8-49fb-a101-1244de770a9c","resolution":{"observed_at":"2026-08-07T12:43:57.079663Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.909172Z","title":"Transformers can do Bayesian inference","venue":null,"work_id":"151a6059-ebf6-41c2-b7c1-a8aac3beef46","year":2022},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.446638Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:a5566f95b7003adecc100e153cc6376431e86db70cc8a23055f9ac6dca0b05c3","observation_id":"7f406b6c-0cd1-413a-90b4-54c3e621fd1c","resolution":{"observed_at":"2026-08-07T12:43:56.941971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.827965Z","title":"PFNs4BO: In-context learning for Bayesian optimization","venue":null,"work_id":"94fbfb99-00b7-49db-8b73-7395bdaf8a31","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.544178Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:8001ab3200fddd33faff03d016807e3e8d1fb3a33c6f599f57330ed654c6b184","observation_id":"1e275b1d-f82c-4ffc-9078-2d3c882d753b","resolution":{"observed_at":"2026-08-07T12:43:56.860832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.758189Z","title":"Normalizing flows for probabilistic modeling and inference.Journal of Machine Learning Research, 22(57), 2021","venue":null,"work_id":"902bb3cb-c3c8-4541-9ea9-cd2925e63166","year":2021},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.676970Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:07e8b504ad7e76130304cd8ab733fb6fa8dd295068caea4dd7a0360d7709c2de","observation_id":"f286c8d7-725d-4435-b1b2-e842087a7e68","resolution":{"observed_at":"2026-08-07T12:43:56.786912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.675996Z","title":"Radev, Ulf K","venue":null,"work_id":"2f43acf5-8e73-4b08-a24a-d574a65ef3c3","year":2020},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.763492Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:21630ffe973a7cf5365f7330504a86d52b9da69e168498be5c5fe9237f159bb8","observation_id":"a2d7330e-6fe5-4d1e-947e-0d1a2e6aec60","resolution":{"observed_at":"2026-08-07T12:43:56.718339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.567512Z","title":"Random features for large-scale kernel machines","venue":null,"work_id":"b4e631c7-1245-4dfb-83d8-9720cccdacf0","year":2007},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:52.882837Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:8d8ca24238a6ac43df6e1ff0f11e984ffbe71c8927a8bb00e125819c03b132c3","observation_id":"fb26c9c5-3b59-43e9-93ac-fd507f241d63","resolution":{"observed_at":"2026-08-07T12:43:56.623938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:53.030155Z","title":"Zero-shot text-to-image generation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.030155Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:7e0c0f6e88aadec039381212a8bb0f0c39666d958da5616da7b0696cf1f7d8cc","observation_id":"a15b807d-1fd8-44f6-870e-4667f0e54463","resolution":{"observed_at":"2026-08-07T12:43:53.030155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:53.118430Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.118430Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:44edb6d92f34949a637f25dda9db0a2433fed1415d5a00dd71e3ae61053df3b2","observation_id":"58edba69-8de3-43dd-b350-7aad39c635ac","resolution":{"observed_at":"2026-08-07T12:43:53.118430Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.481406Z","title":null,"venue":null,"work_id":"d129f14a-e270-48e4-860d-94a44df29fa4","year":2025},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.164461Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:61cb97cc6abe0c989f71e97504c87ff64621510770610cff0991fe07dbbdd8f5","observation_id":"c4455915-f2fe-4cae-abfc-0c358134cb56","resolution":{"observed_at":"2026-08-07T12:43:56.515230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.416664Z","title":"Navigating the protein fitness landscape with Gaussian processes.Proceedings of the National Academy of Sciences, 110(3), 2013","venue":null,"work_id":"cbf8dc49-b47f-46e5-b6ab-9b96800bae46","year":2013},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.229454Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:a9fb78cce21d50eb2091384bafcb80c8aaf0ba5144c9fa7c588e4c74464ee847","observation_id":"910c094b-1334-4d1f-b489-d434bb2e0450","resolution":{"observed_at":"2026-08-07T12:43:56.445527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.345305Z","title":"Application of Bayesian approaches in drug development: starting a virtuous cycle.Nature Reviews Drug Discovery, 22(3), 2023","venue":null,"work_id":"b66a465b-4bfd-4ff3-a523-d08bc916c8ac","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.354256Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:dfb3536efb1563e31a9b2a77c3e3c55193b3da08018d45f4869585c2e15573a8","observation_id":"168d8fb5-bfb5-48cb-b03e-a0f1c134a631","resolution":{"observed_at":"2026-08-07T12:43:56.372016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.243569Z","title":"Adams, and Nando de Freitas","venue":null,"work_id":"ffc88f4d-f051-4ae7-b57d-92ae20074152","year":2016},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.446548Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:a063bc641f1491d34678dba5cad36fb8596e5e2f177ff624a1c3495526f9cb47","observation_id":"29da98de-cef0-4417-b3f8-980d6ca6ad49","resolution":{"observed_at":"2026-08-07T12:43:56.305074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:56.099688Z","title":"Practical Bayesian optimization of machine learning algorithms","venue":null,"work_id":"e4b39f9e-827d-4da8-a852-4ffc530fe9ce","year":2012},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.496253Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:f97d32ee264e697cdceef18821b34b478aa481e1ced2da63f0cc8d45afde23ec","observation_id":"4032a8b4-07aa-434b-9f1a-c5d92f36055c","resolution":{"observed_at":"2026-08-07T12:43:56.159491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.882844Z","title":"normflows: A Pytorch package for normalizing flows.Journal of Open Source Software, 8(86), 2023","venue":null,"work_id":"dc87f587-65d7-4e84-ac84-b1dd82df2df5","year":2023},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.555906Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:fe4f8fa72f812e3701d9e72feb5c31d5e8ea846fb8d553394373268ef53bfc87","observation_id":"46821008-d8e7-4e9f-b0cc-c09f72cf43fa","resolution":{"observed_at":"2026-08-07T12:43:55.983091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.605201Z","title":"On the likelihood that one unknown probability exceeds another in view of the evidence of two samples.Biometrika, 25(3-4), 1933","venue":null,"work_id":"24926785-1123-4140-b85f-121498c8a251","year":1933},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.649730Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:a4655ccd8d147212bb8fd0d862091dc76fb2251433d30e9ec7878bbe64101675","observation_id":"8cea4063-d54b-4966-acfb-a98fa50b1a3a","resolution":{"observed_at":"2026-08-07T12:43:55.723272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.344544Z","title":"Schmid, Sterling G","venue":null,"work_id":"21808e2d-140a-4980-b0a2-3d9ef86fdff4","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.692424Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:52e10455d3cd8b3d0f544e2684cd68a33b13f4c5f88dbaf3d98a1957bd684b90","observation_id":"a974a98e-1b6f-4c3a-9a38-141fc802a067","resolution":{"observed_at":"2026-08-07T12:43:55.458353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:53.719477Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.719477Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:9dd50db53000b671bb6b3c4bfe337ab3a40afe247c173d582844876b286e1791","observation_id":"1634db55-a2dc-4d52-883c-ac3c33fa9e79","resolution":{"observed_at":"2026-08-07T12:43:53.719477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.237347Z","title":"Maximizing acquisition functions for Bayesian optimization","venue":null,"work_id":"495b2991-e561-4675-872e-170892b4504a","year":2018},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.746175Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:19511efdb11d1abb7f10177dba63b1f5ae0762089b2ff476c7ce9f312ee02869","observation_id":"b76d84fc-15da-4618-9276-b2cada4fcce2","resolution":{"observed_at":"2026-08-07T12:43:55.264777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.158055Z","title":"Diff-BBO: Diffusion-based inverse modeling for black-box Optimization","venue":null,"work_id":"72d09d63-f38b-4834-81a9-32e54ec885bc","year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.773368Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:beae27b6b46b3321a0da0992aaf17e261979bcc9084e8c0a69c4f4f660ddf8af","observation_id":"d1dfd820-8f0a-428e-b9d5-df6b0dcd9fcb","resolution":{"observed_at":"2026-08-07T12:43:55.196465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11340","last_updated":"2024-11-21T14:09:12Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T16:42:46Z","title":"OmniGen: Unified Image Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11340","snapshot_observed_at":"2026-08-07T12:43:53.854399Z","title":"Omnigen: Unified image generation.arXiv preprint arXiv:2409.11340, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.854399Z"},"links":{"cited_paper":"/paper/2409.11340","citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:923d2b73d93d5135b929a830e28b58a28a3ed06489b0f02eea9c5d6149abd796","observation_id":"8a02e625-3863-4b23-8586-38e99def730c","resolution":{"observed_at":"2026-08-07T12:43:53.854399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:55.037483Z","title":"An explanation of in-context learning as implicit Bayesian inference","venue":null,"work_id":"3306e643-d438-45f7-9715-e213cfc3b449","year":2022},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:53.932249Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:bfc3340426175d1317df18b99066a5d5f54f794c4d66a85fcc023073a5e387fa","observation_id":"dc3c73b2-4496-4c61-b4b7-51f8b84d4650","resolution":{"observed_at":"2026-08-07T12:43:55.096236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:54.648521Z","title":"Posterior inference with diffusion models for high-dimensional black-box optimization, 2025","venue":null,"work_id":"2872d291-acc0-493d-a338-bf713df3694e","year":2025},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:54.005581Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:82affe7fe83e2fe7d58ef1ff41a646abd478ac0fe023d1cc23e6d20e7dea5e07","observation_id":"7d2b8c3d-9fb6-40f0-aea8-696f099b1873","resolution":{"observed_at":"2026-08-07T12:43:54.840539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:43:54.259183Z","title":"Deep sets","venue":null,"work_id":"21e1c6f6-008a-42ef-b6b2-4a7f06602c3f","year":2017},"citing_paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:54.117306Z"},"links":{"citing_paper":"/paper/2505.23913"},"observation_digest":"sha256:77d952d18e246f2860ee4cbbc483512aa7fd87bf26e7080c90afe42ba66e5532","observation_id":"4e9c6a9a-fdf2-467d-a35e-6df510c009e7","resolution":{"observed_at":"2026-08-07T12:43:54.464797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.23913","last_updated":"2025-05-29T18:07:36Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T12:36:08.371159Z","submitted_at":"2025-05-29T18:07:36Z","title":"Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":39},"total_outbound_references":49},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 inbound Pith citation observations for arXiv:2505.23913."}