{"as_of":"2026-08-09T11:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6e94021bc99dc2dcdccec2543b31afb479fa621dae97d0544078418a77d06730","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":"2026-08-09T06:31:02.800959+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":"2026-08-08T16:22:28.349762Z","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":"2026-08-05T16:11:00.112263Z","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":"sha256:72c559cd35a5bcb2021dd1ae80434ac94af9288e8abdc6fc5710b848cd1b3c9a","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06200","last_updated":"2025-06-03T14:24:01Z","snapshot_observed_at":"2026-08-08T16:22:28.349762Z","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":"2026-08-06T19:57:53.351162Z","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:a122114d9f70dab55c9f0ec3a76b304cc40e3e1b16700dfd1513c78615dae51d","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":"2026-08-08T16:22:28.349762Z","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":"sha256:88ceeefbbd545f5883bed2ec1bf0f97c47475ddbc35f6b6f11092c4542775ab1","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:ac989976d3bcb5a3e8bf8f1dcb72e1a6b00dd3a96ab3224cdc0529eccc91765d","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:e1d96ff540df0eb21bb647ffca70c914ce6f4a8e9deb7f1126a2ffa18c04d0f4","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:66c3da1250f0a7007a45c4c06714615e89482d8268d6fa970407555e7825dd2f","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:3baebc73d816e4be0548b28f5eaf29d6ab706148b053c2eff8c46b7eb21eb9dc","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:0e05fc8a1c03afac5a74f111388b77b0f5be99232fd772ac959c0f264848e4da","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:b58150b242526e7b15af1d2db1278bc54cd4ed8f00e4550bf11aa1320091b8b9","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:77fe03c93738382362538ca5446cd3da840e55a950754477a29a7cab40904cf4","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:20935119dfe4d4839f7725565e7e1e0f93e5829d85a998b761923072ad0b6041","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:827b96789bc8afa6b95154a13f9dc05ef757ec02ee327aed273556fcfbff21a5","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.07776","last_updated":"2025-05-26T16:25:19Z","snapshot_observed_at":"2026-08-05T17:22:27.953993Z","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":"2026-08-08T16:22:28.349762Z","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":"sha256:460640168a4982afd8b03e82df9a825ffe2b0ab3ae6c381adff093a4fe6c28d4","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:b44aace74ae5abc0aec3a7f804200cacfd92dee4cd79b5392c8278fc9ad00c26","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:f1f59947216f199e0c786d71ae390d2404c6735f0dbbb03e3d8350a558cce889","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:63a121de1538b4c5e7cff53a8bbffbb6b606094fe1e7e3208aeabddb046001bb","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:1b71b64d7f97263196e84f05f734edf025c643c1577b713143c811e79a3dbefe","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:84150025172d64740904642bb18037c157e463f7adaeb7ba21543db9ea147017","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:41b18e4add1b37cddcb7880a0c82f0e6c647611fc795ea5fb30fd2cae12673b7","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16936","last_updated":"2025-02-17T04:29:40Z","snapshot_observed_at":"2026-07-06T18:51:02.128594Z","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":"2026-08-08T16:22:28.349762Z","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":"sha256:26372e6bb63434a9bf37efbfd600f7a813244bbd452c912ac2dcf84c8ef63506","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":"2026-08-08T16:22:28.349762Z","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":"sha256:789887911db69086be1dd284ee9e759f4da22245000cd8f9189d61cc67449226","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":"2026-08-08T16:22:28.349762Z","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:c8083b6314c6826420d15b802416b68722c5ac080c4dbe46d490552b1d646542","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:40963d2c1673259b61ad9f7d7ce406db4abbaa856ec9c3b309c2bf6894c2635a","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":"2026-08-08T16:22:28.349762Z","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:a73b2cd6382ffa0b67ea1bb3e5938b3c6e3e4d8d65e805ba91fefd7bb28f6a09","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:9ac6b4a296671808eff4eb83be237f9e00020612cb3ac2a60c4c517ea6c83fa8","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:69993191149879c2bb295c854efe46904b72e88ab7175ee8762709a1d6045189","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:f6b934fc8463d9ba974c5708011da547b5270ee1006f3ad314a9afd42aeccb7d","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:d8100afe5de74d82b997bc38cdb5c31b7cac3830b8637a01d5dbf00fdffbff38","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:3278396de07c3c1ca701245c3c57374e0b6cc1c49cdaca0c858126b12de99da6","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:8e9d42b7451de43506563ad361499678531fc6ba46cfc78f3a50c7b01396a113","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:077f823c48034b0a6ddb4dad0ca2f501a97de318b6d5af8971983559a4cffc1a","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:8a74900bf3f8e2c8e723236e7d58ce27fa50bb6d802e476dc281d771cea376dd","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:5b858a05fda4da4b860d528843c415e7b2118148a6e6791c1a8bf89e69e9cef8","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:e05774e5c5efa936851cfec6f6282d2fb84fe4de8d90066ba4ddd258e758fac2","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:3b29e4d3068862cac83e19c4b76266533a6945ebdffd48ca596b830fdbc51a5a","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:0ca0b6660d66af458dc476f21eb76a160f89a9c17ca0d09550006a6b529dbbaf","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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:cadbbfc76ec224b3bc7be25d2cb64cbaffa19334e6d11b5931d0b12bfa991566","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:0918a9dff0624136046c7384a089f26210af73afc44226b7598f80851bcd43c4","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"sha256:8f7dadebaa94e5ea51463654d26c1b4e70e6417292c15d1863652046eaa137fa","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":"2026-08-08T16:22:28.349762Z","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":"sha256:1e3cca4fe19da01c365a3d03f605787add6114301711524cc1814d081bb44d2d","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 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T16:22:28.349762Z","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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2502.06200."}