{"as_of":"2026-08-12T05:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6886f5478def42d042b028bbac0f132a246ccfa124cd8e403f7e9af8d0201d34","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T16:31:00.171252Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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":"2026-07-30T12:30:53.400656Z","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":"2026-05-11T11:16:03.235051Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"cited_work":{"arxiv_id":"2502.06200","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06200","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Instance-dependent Convergence Theory for Diffusion Models","venue":null,"work_id":"7ca9547d-6060-4912-bd41-dc829a5d9f3c","year":2025},"citing_paper":{"arxiv_id":"2604.10857","last_updated":"2026-04-12T23:47:46Z","snapshot_observed_at":"2026-08-11T14:15:04.322437Z","submitted_at":"2026-04-12T23:47:46Z","title":"Query Lower Bounds for Diffusion Sampling","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T15:04:29.421000Z"},"links":{"cited_paper":"/paper/2502.06200","citing_paper":"/paper/2604.10857"},"observation_digest":"sha256:a7d8cf786710568085bf0d02881724a969a006d31a461f3e4f2864efd230d4b3","observation_id":"ebb8ed3b-a941-4fc0-8283-d8c74157268e","resolution":{"observed_at":"2026-05-11T11:16:03.245743Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06200","snapshot_observed_at":"2026-07-30T12:30:53.400656Z","title":"Proceedings of the 38th Conference on Learning Theory , series =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23788","last_updated":"2026-07-29T05:31:44Z","snapshot_observed_at":"2026-08-09T22:12:32.516790Z","submitted_at":"2026-07-26T18:06:23Z","title":"The Universal Warmup Path: Automatic Preconditioner Selection for HMC","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-07-30T12:30:53.400656Z"},"links":{"cited_paper":"/paper/2502.06200","citing_paper":"/paper/2607.23788"},"observation_digest":"sha256:5cca80830e1ae1643165888ad27abfe1c64976786a1724d307174950a7463070","observation_id":"a800f7a2-45d5-4a63-a277-c0cd9828c65e","resolution":{"observed_at":"2026-07-30T12:30:53.400656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.06200/citation-record","integrity":"/paper/2502.06200/integrity","json":"/paper/2502.06200/citation-record.json","paper":"/paper/2502.06200"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:31:00.648347Z","title":"Faster high-accuracy log-concave sampling via algorithmic warm starts","venue":null,"work_id":"9a584858-8247-4217-b690-76478b9f4ea7","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-08T16:30:59.982502Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:397ca867c62a4ff4e3b73202de8abb5ae6d3468546ef0c5acf602f08df24bba5","observation_id":"9c001a58-0b54-4949-ae5b-f4e70e279f7f","resolution":{"observed_at":"2026-08-08T16:31:00.651959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.638319Z","title":"An introduction to MCMC for machine learning","venue":null,"work_id":"2dd4f481-3c3e-4e95-8446-d80303d6a54f","year":2003},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-08T16:30:59.987610Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:4a1274d42416eeb9461b63d0b3eaf7a62082ca94615afa8858788ae0452ad3db","observation_id":"2961944f-352b-49b0-b8e1-8cae0d43b1f9","resolution":{"observed_at":"2026-08-08T16:31:00.641681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.626087Z","title":"Nearly d-linear convergence bounds for diffusion models via stochastic localization","venue":null,"work_id":"0c7a9055-d804-4cec-b477-5e88eeb81533","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-08T16:30:59.992614Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:ed92bd5f3117546f2fba858e534bd3e70b9c5607394aa458815f9242753deb88","observation_id":"9ba5e1d3-9b28-4682-b927-ca38e1dda26f","resolution":{"observed_at":"2026-08-08T16:31:00.630264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.612009Z","title":"Towards a theory of non-log-concave sampling:first-order stationarity guarantees for Langevin Monte Carlo","venue":null,"work_id":"553009d0-9800-4f5f-9660-c475669de58f","year":2022},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-08T16:30:59.997199Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:564eacf27dc91fd797d67f419ad4119b32a29d3f96e2469544aa4278f1b248c3","observation_id":"ed16ab5d-3924-4537-b575-99cf4efc430c","resolution":{"observed_at":"2026-08-08T16:31:00.615326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.600904Z","title":"On extensions of the Brunn-Minkowski and Prékopa-Leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation","venue":null,"work_id":"fd95f21f-bad1-451e-b995-92a5a86a262e","year":1976},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.002069Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:6795883fa2c70c772d9ec0604f53ab5ef50cf5bd558bc10195232fed7b0794fc","observation_id":"25b36be9-fe92-491d-80eb-d2dee3ac9f9e","resolution":{"observed_at":"2026-08-08T16:31:00.604702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.590117Z","title":"Convergence of Langevin MCMC in KL-divergence","venue":null,"work_id":"667f8095-c617-4a0e-8ef1-3fcbf0b42868","year":2018},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.006907Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:a4f536155a46ddce9263c22db5cf8dc9c752ef3e5b0d232d5669faa5115f25dd","observation_id":"0347a2ad-9cb3-415f-bb13-5dd88bdffc42","resolution":{"observed_at":"2026-08-08T16:31:00.594171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.578713Z","title":"Chatterji, Peter L","venue":null,"work_id":"97148e27-04fb-49ec-b518-18ce9d60395c","year":2018},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.013849Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:88093a5e11fa681453455757a1426d69880eaf72160bb66f001874ab63e67ce9","observation_id":"e5e9efd9-60e1-4738-bf26-9eb6dd4d55e0","resolution":{"observed_at":"2026-08-08T16:31:00.583131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.567847Z","title":"The probability flow ODE is provably fast","venue":null,"work_id":"e161df70-f5a4-4339-a75f-804b4d49bf92","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.019954Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:8fc9429d3114365df399aa245a9f6ed00b8704e45b53ebfb3a2870ec8fd43ea0","observation_id":"0e80bf46-c2dd-4340-b358-215660e20763","resolution":{"observed_at":"2026-08-08T16:31:00.571601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.556425Z","title":"Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions","venue":null,"work_id":"598ec9c5-c052-4136-a2f5-13d98902adc0","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.025421Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:21ab8fcf40214e893401fef28fcb55cf3ca9079cb60ae03cd117de11315823db","observation_id":"e8113617-f6a6-4d66-ad21-a2b347f447ba","resolution":{"observed_at":"2026-08-08T16:31:00.560807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.544343Z","title":"Analysis of Langevin Monte Carlo from Poincar \\'e to log-Sobolev","venue":null,"work_id":"f2bf1bc2-19ac-4db8-ad44-569277d7c324","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.035352Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:688275764ef3b28caf10612492b9d1527a83ad29fc77d3439bc9f02f3f33e14d","observation_id":"9be334e9-9092-4ac2-bb78-d441b310713e","resolution":{"observed_at":"2026-08-08T16:31:00.548213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.07776","last_updated":"2025-05-26T16:25:19Z","snapshot_observed_at":"2026-08-10T19:35:18.724672Z","submitted_at":"2024-11-12T13:19:23Z","title":"On theoretical guarantees and a blessing of dimensionality for nonconvex sampling","version":2},"cited_work":{"arxiv_id":"2411.07776","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.07776","snapshot_observed_at":"2026-08-08T16:31:00.271197Z","title":"On theoretical guarantees and a blessing of dimensionality for nonconvex sampling","venue":"stat.CO","work_id":"698065d2-64bc-4d06-98e4-95a528eced18","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.041323Z"},"links":{"cited_paper":"/paper/2411.07776","citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:c581c18b7940110477437e6ba4cdee1c14a7e59dccedfb19883f79d13c2edab0","observation_id":"ca829c05-ef81-47d2-a01d-98b5b8a5d1a2","resolution":{"observed_at":"2026-08-08T16:31:00.277231Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.533785Z","title":"Log-concave Sampling","venue":null,"work_id":"89bab37c-7f4d-44d8-9bec-fc7d14e0645a","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.053801Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:8487dfcbc923bb349c5497e060a29799d97208bec5d00f933c94c35cb6d32cda","observation_id":"ac6fae17-459e-4326-a0cf-00ed2403e25e","resolution":{"observed_at":"2026-08-08T16:31:00.537805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.522574Z","title":"Optimal dimension dependence of the Metropolis-adjusted Langevin algorithm","venue":null,"work_id":"1a081897-dd0d-4cbc-86f7-82b26f6f5243","year":2021},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.059382Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:0306ec501a8d2070ed90aa4f488ec8a469efebf8f1937d79455218fb7dc754e1","observation_id":"c9efbd34-4fed-4710-8fb2-9bb9878a7fe6","resolution":{"observed_at":"2026-08-08T16:31:00.526595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.508274Z","title":"Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions","venue":null,"work_id":"c2174142-1085-45fb-9fe2-524d4c62a8fd","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.066277Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:75c23212b5cc11abfd6452f49b2dc9b7cf63d755e0b9bf01c66fe7393bbe0699","observation_id":"b59898e2-6ccf-45d1-8e26-6a1cb77b72ea","resolution":{"observed_at":"2026-08-08T16:31:00.513234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.494904Z","title":"Simulation and Monte Carlo : With applications in finance and MCMC","venue":null,"work_id":"44236e78-58c2-44d7-be58-5d8eb8cc5ce7","year":2007},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.071096Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:d72ac0554293e49062bd90cbf80de5529956c403590b5dd194611ac3eae1e0cf","observation_id":"765a7124-0858-4cbe-9ac6-db03debec5d7","resolution":{"observed_at":"2026-08-08T16:31:00.498161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.484078Z","title":"Log-concave sampling: Metropolis-Hastings algorithms are fast","venue":null,"work_id":"e9814982-c726-463b-b40a-8944bb4f0aba","year":2019},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.074338Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7e27ed0de6e054f2737c70a5e3609b2642bfb8e32f8090509e46de02ef2a5a2a","observation_id":"0cb617ca-fe7a-40a4-adfe-f8859cd0c543","resolution":{"observed_at":"2026-08-08T16:31:00.487592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.474141Z","title":"On sampling from Ising models with spectral constraints","venue":null,"work_id":"0b561605-8e4d-4366-9806-28493a2a2089","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.078273Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:a7e8b8933c8c14ae96cc9e2d416856864909eab2bd96a63d6c0bc2142c015f62","observation_id":"ecc2382f-1edb-4d78-bcc2-9251c8053e9e","resolution":{"observed_at":"2026-08-08T16:31:00.477081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16936","last_updated":"2025-02-17T04:29:40Z","snapshot_observed_at":"2026-08-10T02:14:41.945866Z","submitted_at":"2024-07-24T02:15:48Z","title":"Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.16936","snapshot_observed_at":"2026-08-08T16:31:00.082076Z","title":"Provable benefit of annealed Langevin Monte Carlo for non-log-concave sampling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.082076Z"},"links":{"cited_paper":"/paper/2407.16936","citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:0d3094f10d72be5ec40fd2b37e5d51266200c6bc3b5c9dfe34b986cce193dc45","observation_id":"d480154c-89af-4370-ba85-5a13d4b2edea","resolution":{"observed_at":"2026-08-08T16:31:00.082076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.03237","last_updated":"2026-04-23T09:32:23Z","snapshot_observed_at":"2026-07-06T14:59:14.951471Z","submitted_at":"2023-03-06T15:53:44Z","title":"Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.03237","snapshot_observed_at":"2026-08-08T16:31:00.085779Z","title":"Convergence rates for non-log-concave sampling and log-partition estimation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.085779Z"},"links":{"cited_paper":"/paper/2303.03237","citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7cfc10cf7f762768a60b0747293dad764ce0d8d627d41878efb5507820c74385","observation_id":"2ec0331f-ff3c-43dd-8846-c6ae4e9e11d2","resolution":{"observed_at":"2026-08-08T16:31:00.085779Z","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":"2026-08-08T16:31:00.465225Z","title":"A separation in heavy-tailed sampling: Gaussian vs","venue":null,"work_id":"aa34491d-f1f5-4fd6-84c8-08b10805ac43","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.090669Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:8785f8809f5929358e0f893fde800f3eceaa72f2e4692d293fc8da76e2e9efce","observation_id":"3fd34f8c-e0f6-4f47-970d-a39e7a5c30b3","resolution":{"observed_at":"2026-08-08T16:31:00.468331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.09075","last_updated":"2024-11-22T18:46:46Z","snapshot_observed_at":"2026-07-06T19:50:05.918060Z","submitted_at":"2024-11-13T23:03:43Z","title":"Weak Poincar\\'e Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.09075","snapshot_observed_at":"2026-08-08T16:31:00.094068Z","title":"Weak Poincar 'e inequalities, simulated annealing, and sampling from spherical spin glasses","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.094068Z"},"links":{"cited_paper":"/paper/2411.09075","citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7722bda291302987c7a5fd973c47e37451748999f9baafdc84af89fbf2844b12","observation_id":"76adaa45-f03a-49af-b956-9f88c7b8dc24","resolution":{"observed_at":"2026-08-08T16:31:00.094068Z","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":"2026-08-08T16:31:00.454912Z","title":"Zeroth-order sampling methods for non-log-concave distributions: Alleviating metastability by denoising diffusion","venue":null,"work_id":"7cd0c597-b2c7-4b04-814d-e57791b56be6","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.098402Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:f43dff9fa98e44e212a6ebb0182877e06494cafde6e28a308f3917724c403d64","observation_id":"d1bcc525-2f9b-48ae-9d5e-e5762aae540a","resolution":{"observed_at":"2026-08-08T16:31:00.458225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.445558Z","title":"Faster sampling without isoperimetry via diffusion-based Monte Carlo","venue":null,"work_id":"7e618b86-5444-4fc2-b981-d27a4ad3451f","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.102387Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:9a7a2900793593f47bc1f422eeb6c15a7017baf98742b3f917e7040d378cf5a8","observation_id":"a8cfb972-2cbf-490e-86e6-c8b534eb8373","resolution":{"observed_at":"2026-08-08T16:31:00.448910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.435228Z","title":"Sampling approximately low-rank Ising models: MCMC meets variational methods","venue":null,"work_id":"9f45bedb-ee49-4aab-8d0c-86675a4255f3","year":2022},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.107105Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7630c7738415c1a0209cba89e6f50c204adb5f48b67e93e163c0aa24ff1190f3","observation_id":"d9085ed3-6883-4ef3-a299-2f81f350f17b","resolution":{"observed_at":"2026-08-08T16:31:00.439362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.425851Z","title":"Statistical mechanics: algorithms and computations , volume 13","venue":null,"work_id":"0629bdb2-875b-423e-99b3-ef3f3649dd38","year":2006},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.112176Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:6dce2d18fe6e1d35a691d2254e518857bb15b6be6bb4c7ff878fc3c94c9afd35","observation_id":"5cb68c46-51dd-48b9-b0eb-7f9c3fac4329","resolution":{"observed_at":"2026-08-08T16:31:00.429266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.413754Z","title":"A guide to Monte Carlo simulations in statistical physics","venue":null,"work_id":"292ee5b7-6a43-4211-85a4-0fb32002907f","year":2021},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.116609Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:b19f404fb8ef4dbc7e38cd23a34e435ca29a1d6e46d8d794013724074cfb063b","observation_id":"1526721d-2721-4b5c-8f37-cbce81c96429","resolution":{"observed_at":"2026-08-08T16:31:00.417438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.402062Z","title":"Concise formulas for the area and volume of a hyperspherical cap","venue":null,"work_id":"c24045bd-eb4f-438a-9fe3-9dbe8209d00d","year":2010},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.121103Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:1722ea393a5c007686f65fda0fc506c3a2ec933ce555800fef55bfd3ce0a1e6e","observation_id":"7c6b3965-b468-46e8-b617-3507cca333f6","resolution":{"observed_at":"2026-08-08T16:31:00.406006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.390560Z","title":"Convergence of score-based generative modeling for general data distributions","venue":null,"work_id":"35bf9b86-0a0b-4787-bb89-32d6c8a53e82","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.125704Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:c90fe979039cc38f0a944b9aa0e2f21dc809d3daec7b90e0c0995fd75a0876f1","observation_id":"eb7f09c2-6421-44fe-b4ba-4d832ed100ce","resolution":{"observed_at":"2026-08-08T16:31:00.395305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.380588Z","title":"Universal approximation using well-conditioned normalizing flows","venue":null,"work_id":"46c72a10-912b-4034-8c7f-f18b3fbe2aab","year":2021},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.130381Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7f115e50055ca5e1010b5e01449b1e00ffd7ad59b8f84380452a6e5ad9b0f00b","observation_id":"cd03e1b3-1d19-4edc-922b-69107111e2f2","resolution":{"observed_at":"2026-08-08T16:31:00.384081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.367938Z","title":"Contraction and convergence rates for discretized kinetic Langevin dynamics","venue":null,"work_id":"e41afaee-22f8-4e54-bc8a-151a549a5e0d","year":2024},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.135034Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:ce9256cdff82db85fc7e65579f7ed0ecfe54034475e9181f5fb51392d706d76a","observation_id":"ca7f4fa0-d7ce-44dd-a6f7-9d72995da74c","resolution":{"observed_at":"2026-08-08T16:31:00.371973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.357517Z","title":"Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering Langevin Monte Carlo","venue":null,"work_id":"6587717f-fb72-4dc1-98fa-17f90bef8954","year":2018},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.138797Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:f4a90d1a0df8663d70db9cc1668ddf6bd57ecaba0041756b4a1dd7bba0f23029","observation_id":"cb97a0a0-673f-4cf8-9e9d-6b7aa4b5510a","resolution":{"observed_at":"2026-08-08T16:31:00.361152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.345933Z","title":"Sampling can be faster than optimization","venue":null,"work_id":"c2f4a33d-57a9-45aa-bdc8-4ca07e61a5da","year":2019},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.143636Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:33418cd34ab0f020837ddd5950744fa59145c58a7318767575b386d32259de87","observation_id":"961fbe79-ea14-4fd8-ba4c-cdbf87c948b8","resolution":{"observed_at":"2026-08-08T16:31:00.351192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.332346Z","title":"Towards a complete analysis of Langevin Monte Carlo : Beyond Poincar \\'e inequality","venue":null,"work_id":"92d38471-8ec4-41cb-bb3a-49025d58ce0d","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.147500Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:9b781f74984bb967a9f0b8b120886da0b5551d8f0c6181c34d422ec554765835","observation_id":"24cffbfe-fa0e-441f-a00c-13bbe7276015","resolution":{"observed_at":"2026-08-08T16:31:00.336557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.321240Z","title":"Exponential convergence of Langevin distributions and their discrete approximations","venue":null,"work_id":"a75b385d-2e20-4b11-859e-4d50ecc836a0","year":1996},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.152273Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:7dcc82e2e8bb815ccfaa5b79777caa2f2c810ff9a9d2a9152a47ebaf0f45eb1e","observation_id":"0dd09a11-69fe-470e-96bc-c7b1b5633f96","resolution":{"observed_at":"2026-08-08T16:31:00.324654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.307934Z","title":"The randomized midpoint method for log-concave sampling","venue":null,"work_id":"5f5f38b5-85c4-42ca-bc9c-588478e86804","year":2019},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.157332Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:b4006d3329584f195db3b4f3a00cb112b40d0a6de3713403bd8edb7900d14b04","observation_id":"2b5a4a62-4659-423a-97fb-b97732b33ae1","resolution":{"observed_at":"2026-08-08T16:31:00.312555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T16:31:00.297019Z","title":"Rapid convergence of the unadjusted Langevin algorithm: Isoperimetry suffices","venue":null,"work_id":"58bc6757-163e-43fb-a325-98b8bdf91605","year":2019},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.161847Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:4b64d42ec6ac9353285e9e5653bbd596d91e088ab81caacfda225af75200744a","observation_id":"8d82ce4c-c6c2-4b8c-be2e-250a39b001a7","resolution":{"observed_at":"2026-08-08T16:31:00.300574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.01469","last_updated":"2019-11-04T19:57:38Z","snapshot_observed_at":"2026-08-03T12:52:18.612214Z","submitted_at":"2019-11-04T19:57:38Z","title":"Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.01469","snapshot_observed_at":"2026-08-08T16:31:00.166278Z","title":"Proximal Langevin algorithm: Rapid convergence under isoperimetry","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.166278Z"},"links":{"cited_paper":"/paper/1911.01469","citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:5866f613004dd2500ea32e90bde1539d04dcd3a4353304c5f18a2d02c126dfd2","observation_id":"132f6fe9-86e2-488a-97b9-cb07c7e62d77","resolution":{"observed_at":"2026-08-08T16:31:00.166278Z","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":"2026-08-08T16:31:00.285822Z","title":"Improved discretization analysis for underdamped Langevin Monte Carlo","venue":null,"work_id":"3f7269b7-c2fd-4ef0-9dbb-b4e3d2c3cf42","year":2023},"citing_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-08T16:31:00.171252Z"},"links":{"citing_paper":"/paper/2502.06200"},"observation_digest":"sha256:d3b622608e8c539d7bb7bf06989baf0e69fbf84b6e4cea11d375375d8606cf9f","observation_id":"276fad87-7d66-47c2-a7ef-2174e5252bcd","resolution":{"observed_at":"2026-08-08T16:31:00.289359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","latest_version":3,"primary_category":"cs.DS","snapshot_observed_at":"2026-08-10T11:17:47.682098Z","submitted_at":"2025-02-10T06:54:16Z","title":"On the query complexity of sampling from non-log-concave distributions"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":1,"verified_fuzzy":33},"total_outbound_references":38},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2502.06200."}