{"as_of":"2026-08-09T12:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66b1cc6150f9c5ce67a8246b6841bc8dd2d9fb536bdc12688f68327741f254f5","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":19,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T12:44:54.316970Z","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":"2026-07-04T12:49:52.480137Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-09T12:44:54.316970Z","title":"Stochastic Runge-Kutta methods: Provable acceleration of diffusion models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02305","last_updated":"2025-06-24T03:42:23Z","snapshot_observed_at":"2026-08-09T12:34:18.054808Z","submitted_at":"2025-02-04T13:19:21Z","title":"Information-Theoretic Proofs for Diffusion Sampling","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T12:44:54.316970Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2502.02305"},"observation_digest":"sha256:a89e9253c80299ff98df7bf1f3f4c5b48c6257c68fa7e9bcc075044c96f996c6","observation_id":"31198262-f173-4234-a78a-fc99f01641e1","resolution":{"observed_at":"2026-08-09T12:44:54.316970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-08T21:18:48.953590Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04849","last_updated":"2025-02-07T11:37:51Z","snapshot_observed_at":"2026-08-08T21:10:33.992582Z","submitted_at":"2025-02-07T11:37:51Z","title":"Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-08T21:18:48.953590Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2502.04849"},"observation_digest":"sha256:868bfadb1e275807babc547aa3e0f5a7afd415e372d5456868eaeda607778bd6","observation_id":"8ca354c6-8cdb-4f3d-82b6-9941090f8f73","resolution":{"observed_at":"2026-08-08T21:18:48.953590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-07T10:54:50.253257Z","title":"Stochastic runge-kutta methods: Provable accelera- tion of diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03979","last_updated":"2025-06-05T04:27:46Z","snapshot_observed_at":"2026-08-08T12:18:48.758557Z","submitted_at":"2025-06-04T14:09:25Z","title":"Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach","version":2},"reference_index":170,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:50.253257Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2506.03979"},"observation_digest":"sha256:d317ed2947512980f5bc12d258caafcc64936863c5161a722503fa26a2367558","observation_id":"0859bbfd-4f79-483b-8db5-25f4346ae444","resolution":{"observed_at":"2026-08-07T10:54:50.253257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-07T04:51:16.626327Z","title":"Stochastic runge-kutta methods: Provable acceleration of diffusion models.CoRR, arXiv:2410.04760,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09681","last_updated":"2025-06-11T12:55:24Z","snapshot_observed_at":"2026-08-07T04:40:20.996084Z","submitted_at":"2025-06-11T12:55:24Z","title":"Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:51:16.626327Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2506.09681"},"observation_digest":"sha256:a0d028ce76d3c11f4a225492de3c3fc2020f28ba79130ebf4d82250dc6e95d4f","observation_id":"057bcbcc-6bc7-4b6d-8652-c171eddc28cf","resolution":{"observed_at":"2026-08-07T04:51:16.626327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-07T00:49:49.229674Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13061","last_updated":"2025-08-14T01:01:23Z","snapshot_observed_at":"2026-08-08T23:15:07.376140Z","submitted_at":"2025-06-16T03:09:25Z","title":"Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T00:49:49.229674Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2506.13061"},"observation_digest":"sha256:b99d2f18ac8a2247b44dbf221a8650edc1f47fd5fb4aa113e1e4065eedaae5fb","observation_id":"965a4991-3b57-4885-ac3d-37eae8fd0758","resolution":{"observed_at":"2026-08-07T00:49:49.229674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-06T21:45:17.122179Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.24042","last_updated":"2025-08-13T15:05:42Z","snapshot_observed_at":"2026-08-08T09:40:09.921901Z","submitted_at":"2025-06-30T16:49:03Z","title":"Faster Diffusion Models via Higher-Order Approximation","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T21:45:17.122179Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2506.24042"},"observation_digest":"sha256:b6cd997668ec5f059de7bbfbb6793abe5365743cbde9d9a29da7f5c301f9f9d7","observation_id":"3e1b204b-011f-4d1c-b2ba-5fe0f566db50","resolution":{"observed_at":"2026-08-06T21:45:17.122179Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-06T16:49:30.261633Z","title":"Stochastic Runge–Kutta methods: Provable acceleration of diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12791","last_updated":"2025-07-17T05:05:27Z","snapshot_observed_at":"2026-08-09T03:14:51.610895Z","submitted_at":"2025-07-17T05:05:27Z","title":"Analysis of Langevin midpoint methods using an anticipative Girsanov theorem","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:49:30.261633Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2507.12791"},"observation_digest":"sha256:7c4efc7a825657e59a4dc2a55e526b10083104eb495dcbd35ee905c445ecc626","observation_id":"230d51b5-a8af-4d55-828c-32e937cf612c","resolution":{"observed_at":"2026-08-06T16:49:30.261633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2509.01629","last_updated":"2026-05-16T04:39:44Z","snapshot_observed_at":"2026-08-02T10:11:34.180683Z","submitted_at":"2025-09-01T17:16:34Z","title":"Lipschitz-Guided Design of Interpolation Schedules in Generative Models","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-21T21:53:15.115078Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2509.01629"},"observation_digest":"sha256:85b1b3bd0ba3716128ebb34e471e98cedbb9664b45c68ad28455211492c1441c","observation_id":"01d0c389-277e-4ebe-9818-91b3c64a068b","resolution":{"observed_at":"2026-05-21T21:54:22.853473Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-04T10:54:42.491492Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.09685","last_updated":"2026-06-25T22:49:25Z","snapshot_observed_at":"2026-08-05T22:55:25.809841Z","submitted_at":"2025-10-09T04:08:23Z","title":"Deep Neural Networks Inspired by Differential Equations","version":2},"reference_index":260,"source":"pdf_text","source_observed_at":"2026-08-04T10:54:42.491492Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2510.09685"},"observation_digest":"sha256:4ed7a3a9a630f9562ea1231dea41c507dd0360fc5ac2cf7075cc38ad8163ff03","observation_id":"dde522a2-879c-4a04-8bff-23bb7b4ddc02","resolution":{"observed_at":"2026-08-04T10:54:42.491492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2601.18681","last_updated":"2026-05-08T00:14:56Z","snapshot_observed_at":"2026-07-06T22:43:02.453697Z","submitted_at":"2026-01-26T16:56:40Z","title":"ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T10:42:23.768313Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2601.18681"},"observation_digest":"sha256:3868801778c2cce2a2c4ead9b64c9548541edd9e4599e3043d6b323860ab9736","observation_id":"63dbf2f6-4835-497c-ad08-2a1102ebed82","resolution":{"observed_at":"2026-05-16T10:42:45.277922Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-08-03T04:22:33.501474Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.05533","last_updated":"2026-06-18T02:47:04Z","snapshot_observed_at":"2026-08-09T01:17:57.736271Z","submitted_at":"2026-02-05T10:46:20Z","title":"Conditional Diffusion Guidance under Hard Constraint: A Stochastic Analysis Approach","version":3},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-03T04:22:33.501474Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2602.05533"},"observation_digest":"sha256:804560ba47414c727e206b487241b88542a3111de9de5d81766f15df4013b3a8","observation_id":"7d1d6b8a-0d20-4000-9800-070a049bb6cb","resolution":{"observed_at":"2026-08-03T04:22:33.501474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"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":20,"source":"pdf_text","source_observed_at":"2026-05-10T15:04:29.421000Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2604.10857"},"observation_digest":"sha256:8302161a3d6a298445a70adc86536f79b5d67b6af5f26ac8848ffcc831e9d1da","observation_id":"af47b4f1-c9d0-4d47-8eb1-22613966381f","resolution":{"observed_at":"2026-05-11T11:16:03.223221Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2605.07220","last_updated":"2026-05-22T01:01:28Z","snapshot_observed_at":"2026-08-03T23:09:26.798712Z","submitted_at":"2026-05-08T04:12:02Z","title":"On the Robustness of Distribution Support under Diffusion Guidance","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-05-11T02:27:44.244764Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2605.07220"},"observation_digest":"sha256:0e0fe6914b26130599df52f6a2c71abdaa1c86d38c1ca3e9c730562be99afafa","observation_id":"5a268f76-c9dc-4abb-b08e-cc4769316429","resolution":{"observed_at":"2026-05-11T03:30:57.377543Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2605.07220","last_updated":"2026-05-22T01:01:28Z","snapshot_observed_at":"2026-08-03T23:09:26.798712Z","submitted_at":"2026-05-08T04:12:02Z","title":"On the Robustness of Distribution Support under Diffusion Guidance","version":2},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-05-25T06:34:46.801241Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2605.07220"},"observation_digest":"sha256:353f9fc3f61a0f1e73ab4e443d0bb06af1be06dbac98cbe97d02456c70344982","observation_id":"a165dd10-765e-4a2a-ab21-f0792b453cc0","resolution":{"observed_at":"2026-05-25T06:35:24.717006Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2605.27352","last_updated":"2026-05-26T17:52:28Z","snapshot_observed_at":"2026-07-06T23:37:02.891611Z","submitted_at":"2026-05-26T17:52:28Z","title":"From Scores to Gibbs Correctors: Accelerating Uniform-Rate Discrete Diffusion Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T18:55:55.974028Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2605.27352"},"observation_digest":"sha256:508f41fc5db23e714ca3a178765f945451af43b4f94f585dee01b7b507952b5b","observation_id":"6861bcf7-204d-463b-8fa1-df5f8d300ef0","resolution":{"observed_at":"2026-06-29T19:03:51.428834Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2605.30332","last_updated":"2026-05-28T17:58:13Z","snapshot_observed_at":"2026-08-06T04:50:39.092164Z","submitted_at":"2026-05-28T17:58:13Z","title":"Colored Noise Diffusion Sampling","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-06-29T07:47:44.501736Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2605.30332"},"observation_digest":"sha256:bf8fc1cd3b4ee199541919a2acae3457d998b9d59852e3fa347e813bd3015234","observation_id":"7b006d6a-b3ad-4af8-9299-fd1f460dcff0","resolution":{"observed_at":"2026-06-29T07:53:13.763899Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2606.23627","last_updated":"2026-06-22T17:20:56Z","snapshot_observed_at":"2026-08-07T05:20:53.273007Z","submitted_at":"2026-06-22T17:20:56Z","title":"Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-06-26T05:56:29.406425Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2606.23627"},"observation_digest":"sha256:97a2df6247678f8f919465993579629100e4f93932ccacace82d293cfc785c26","observation_id":"6dec54f3-720b-4f47-b489-279f7f7d0bc6","resolution":{"observed_at":"2026-07-04T12:49:52.481694Z","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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.04760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-04T12:49:52.480137Z","title":"arXiv preprint arXiv:2410.04760 , year=","venue":null,"work_id":"8d71aa26-edda-4d50-8d5b-7cb0a15922b5","year":2024},"citing_paper":{"arxiv_id":"2607.02137","last_updated":"2026-07-03T02:14:28Z","snapshot_observed_at":"2026-08-08T05:30:20.123996Z","submitted_at":"2026-07-02T13:13:19Z","title":"ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-03T17:14:04.821073Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2607.02137"},"observation_digest":"sha256:3f0053215512c51455e07a2f130f557a551be9f8222efbd97dc998246448a4ba","observation_id":"690b4b69-88d7-440c-9adb-99b6ef70a166","resolution":{"observed_at":"2026-07-03T17:18:43.060408Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2410.04760","last_updated":"2024-10-07T05:34:51Z","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04760","snapshot_observed_at":"2026-07-12T08:25:48.021715Z","title":"32 Qinsheng Zhang and Yongxin Chen","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02137","last_updated":"2026-07-03T02:14:28Z","snapshot_observed_at":"2026-08-08T05:30:20.123996Z","submitted_at":"2026-07-02T13:13:19Z","title":"ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-12T08:25:48.021715Z"},"links":{"cited_paper":"/paper/2410.04760","citing_paper":"/paper/2607.02137"},"observation_digest":"sha256:3c9cc0c6f21cb6a67df66507974fcdf2394700ebbd98815c121d658ebff110d7","observation_id":"a8fcd14c-aff9-4134-b52e-616974131ccf","resolution":{"observed_at":"2026-07-12T08:25:48.021715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.04760/citation-record","integrity":"/paper/2410.04760/integrity","json":"/paper/2410.04760/citation-record.json","paper":"/paper/2410.04760"},"outbound":[],"paper":{"arxiv_id":"2410.04760","last_updated":"2024-10-07T05:34:51Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-06T04:32:12.204479Z","submitted_at":"2024-10-07T05:34:51Z","title":"Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+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 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2410.04760."}