{"as_of":"2026-08-13T05:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3495b79bb81bbb79c64d909fa6bcb91d9395432ab7c86df3c1677eb58c425d25","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T12:29:16.215618Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T23:33:07.718877Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.06553","snapshot_observed_at":"2026-07-31T23:33:07.718877Z","title":"arXiv preprint arXiv:2605.06553 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.23937","last_updated":"2026-07-27T02:19:41Z","snapshot_observed_at":"2026-08-04T04:51:45.058855Z","submitted_at":"2026-07-27T02:19:41Z","title":"Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-31T23:33:07.718877Z"},"links":{"cited_paper":"/paper/2605.06553","citing_paper":"/paper/2607.23937"},"observation_digest":"sha256:8b0b0f2492088445821adef9826eafeee25b8e0a86171c2c596198d69bead341","observation_id":"5608cc70-e42c-42ae-976e-e058fd87ead4","resolution":{"observed_at":"2026-07-31T23:33:07.718877Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2605.06553/citation-record","integrity":"/paper/2605.06553/integrity","json":"/paper/2605.06553/citation-record.json","paper":"/paper/2605.06553"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"URL https://huggingface.co/black-forest-labs/ FLUX.1-dev","venue":null,"work_id":"79e31b68-6aad-4af6-8ad1-51c02f4783de","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:4d69c9c34f87a58792d914700f1147a9c64c9b1cf55b25fc42ad077a2b126ede","observation_id":"499bfaf8-d9e4-4c93-b45e-df786ba1ba06","resolution":{"observed_at":"2026-05-26T13:17:49.536796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-07-08T03:54:30.820092Z","title":"Building normalizing flows with stochastic interpolants","venue":null,"work_id":"74430e64-78a6-4f67-acfb-ddaf4f22275f","year":2023},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:647deb5a8d8f3eb204ee9225a19cbd331f5c29077eb974657e3b0f6f69486d27","observation_id":"0c42d4e2-33c9-4c63-852d-cdc8bbd7fc45","resolution":{"observed_at":"2026-05-26T13:17:49.526217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/0304-4149(82","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T07:30:41.519369Z","title":"Anderson","venue":null,"work_id":"12a993ad-501b-4b2a-b16d-25fd87f6f9f6","year":1982},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:192e11670ce98ea15486bafa15799db00302f94b51df48e008f1f206f5e0ca64","observation_id":"2dcc1c73-57c1-4860-bcae-46dbb4daabce","resolution":{"observed_at":"2026-05-08T21:39:15.303899Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-07-09T08:26:05.754154Z","title":"Structured denoising diffusion models in discrete state-spaces.Advances in neural information processing systems, 34:17981–17993","venue":null,"work_id":"b3c340e2-b557-4352-95ba-6967124a292d","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:6f503f3f49e8f0a10c1d62bd32985324ae5d17e42f6945989e9cf720ca8df811","observation_id":"c4a9e3f2-c4b3-49f0-81e3-236766f365e6","resolution":{"observed_at":"2026-05-26T13:17:49.511251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Jaakkola","venue":null,"work_id":"bd3ec681-ab0a-4418-8ffa-c3a448dcf88d","year":2023},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:9a4aa49799c8a4810bade0897776ef33bfebd1883d2cec20bb0abb010db399a9","observation_id":"f4324867-bc68-40e1-9a87-c19a179e3e4c","resolution":{"observed_at":"2026-05-26T13:17:49.514893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Jaakkola","venue":null,"work_id":"bd63128b-1954-4c25-837a-14b555d9e216","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:63e4e960c7b5346d0808133effd980e3ee9cfc0f4733554b93d2c51cfb656cd0","observation_id":"d861d945-e0e6-48cc-96d3-d197f1f94cbc","resolution":{"observed_at":"2026-05-26T13:17:49.503964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Vision transformers need registers","venue":null,"work_id":"dbc603dd-ae9e-4f66-bf8d-2bcf602f6334","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:603679af3deae6f6b5ee1596565042194e40db8e5cf6d95a2a9faaf33dc8aada","observation_id":"3eb039c3-87aa-4e8f-83ea-cc9bcc3f7095","resolution":{"observed_at":"2026-05-26T13:17:49.511007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Diffusion models beat GANs on image synthesis","venue":null,"work_id":"303770ea-8c89-4974-bf8e-0056e9bd8c8d","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:d1a24404cb82e07460fe116160e31fca2e3a46797b7be339fe19813b82391446","observation_id":"09588002-00a9-4f6d-84b4-9cd2ad717230","resolution":{"observed_at":"2026-05-26T13:17:49.500598Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"stable/2323956","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Yilun Du, Shuang Li, Joshua Tenenbaum, and Igor Mordatch","venue":null,"work_id":"025e78f0-da85-48fd-891d-f69ee62f2017","year":2019},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:f47299bdfba222e72d65aac64d9f163d47b3fdb3b27a81076ef58fbf808eb0ea","observation_id":"19992eea-4398-455d-98e3-91f18ec5b68e","resolution":{"observed_at":"2026-05-11T19:16:07.381790Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.00090","last_updated":"2026-05-01T04:44:00Z","snapshot_observed_at":"2026-08-11T03:47:42.431102Z","submitted_at":"2025-12-31T19:47:49Z","title":"It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models","version":2},"cited_work":{"arxiv_id":"2601.00090","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.00090","snapshot_observed_at":"2026-07-04T13:29:52.047333Z","title":"It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models","venue":"cs.CV","work_id":"6012f0d8-60c0-4740-ae1a-802144aaaacc","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"cited_paper":"/paper/2601.00090","citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:f038bce1b130251da4e0e639b25e4d06c4e398f53752c8110b686c56ea48e668","observation_id":"7050fc7f-f2a7-4624-910d-4475222a3418","resolution":{"observed_at":"2026-05-11T19:16:07.397917Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2021.emnlp-main.595","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T18:14:59.011669Z","title":"doi: 10.18653/v1/2021.emnlp-main.595","venue":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","work_id":"15cbe62c-2a12-4134-a55d-a9ae4bfc767b","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:e50f7a2b653764f48bb688fa1fd1797f3416df786f295c03162b7e81ed238397","observation_id":"95eace32-f837-4051-a008-09c2c145332b","resolution":{"observed_at":"2026-05-08T21:39:15.307608Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-06T21:38:19.413127+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-06T21:38:19.413127+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equi- librium","venue":null,"work_id":"0aadd9e0-9f29-4ad4-b33e-7158afe946c8","year":2017},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:c319b560f218f204b927f5b8cedcb678e2c7d3f5697fa0928742baca351eae4b","observation_id":"d48732ea-536f-4e36-996f-36abe86c135e","resolution":{"observed_at":"2026-05-26T13:17:49.507711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":"068afafc-f1e6-4b79-83e7-4a5a7b90e841","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:2256a27875db0f758cdc0cc1176d1f764e705b2af9ff6b8f4563bdb2b2f173fd","observation_id":"fa40809a-334e-4f5d-9db4-0987fa88019b","resolution":{"observed_at":"2026-05-26T13:17:49.518462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851","venue":null,"work_id":"d13fa420-783d-4f8c-afff-897c0232b4ee","year":2020},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:b88be6d63666d8895c47b21bd91b30523469e94649e498eb26ee37095ab69537","observation_id":"049ad4b5-a9ca-4978-b7ae-f671c83f82af","resolution":{"observed_at":"2026-05-26T13:17:49.525955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Equivariant diffusion for molecule generation in 3D","venue":null,"work_id":"7584c1ea-ef39-4daf-be41-955fbb05a290","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:916433e3c3620a5b829268ec73028d4c4feb3caf178e7ae1f1819cd642a60a7e","observation_id":"046e35ea-9d7e-4e59-b38d-806b3711907f","resolution":{"observed_at":"2026-05-26T13:17:49.557254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Simulation-free differential dynamics through neural conservation laws","venue":null,"work_id":"aba3adea-96ab-46e6-a099-6b406a089ec0","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:dfb635e19c7c28aa4d27161b9beab40d2f388afe36beb120338acbf3cc93362e","observation_id":"637b3449-64fd-47c3-830a-de210229a88d","resolution":{"observed_at":"2026-05-26T13:17:49.547287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"An information-theoretic evaluation of generative models in learning multi-modal distributions.Advances in Neural Information Processing Systems, 36:9931–9943","venue":null,"work_id":"df5fcefd-c62c-4232-afec-747cd70733e7","year":2023},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:a6ad9cde54905150df16fda7e7586b90f0628a18432243f82e0640b77d4c2346","observation_id":"e2eb905d-27c1-4508-a430-4ffa74e79013","resolution":{"observed_at":"2026-05-26T13:17:49.483449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"SPARKE: Scalable prompt- aware diversity and novelty guidance in diffusion models via RKE score","venue":null,"work_id":"93b2367d-f976-42b6-a393-9ae9b2c1ea60","year":2026},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:a8b677175dc7e71803a71311b181844d949d1b3ab49dd7b990a69ccc6a250385","observation_id":"8ef16559-a3fa-434b-8f73-4a3b655d4dd4","resolution":{"observed_at":"2026-05-26T13:17:49.495457Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Rethinking FID: Towards a better evaluation metric for image generation","venue":null,"work_id":"8e64e60d-902d-48f7-9386-b18467ce4e14","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:e7384e3ddb5a34aca8fc90993a7ddb0a7ecf776c39f8a473a90c6fbf77193e2f","observation_id":"5754901b-d96a-48d7-b872-4f0f6f1b2c8b","resolution":{"observed_at":"2026-05-26T13:17:49.472780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Torsional diffusion for molecular conformer generation.Advances in neural information processing systems, 35:24240–24253","venue":null,"work_id":"6246a47e-a11c-44a1-99a3-c6b1de570ca8","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:28afc1ca198a25c53e75a312b9d6b06c38cdb1c9d1a7501cb7b50c90e346d228","observation_id":"f463b6b1-41f6-4d21-9c5e-ba5a6ce77c57","resolution":{"observed_at":"2026-05-26T13:17:49.543935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Diverse text-to-image generation via contrastive noise optimization","venue":null,"work_id":"961984c3-657b-4372-a651-687cf23bc934","year":null},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:8326515abca12bae79f89e8f9cb2a22bfea1aa41c329f6a64c96064fb024a170","observation_id":"5190adef-6bc7-41c9-9800-3b51fe62ee13","resolution":{"observed_at":"2026-05-26T13:17:49.503263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"60797e4f-08c8-4713-80dc-f8703ac0eb35","year":null},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:d2cac53dd61eb8ec89a7e108f42efc3a2695e37003d283a6125d9046eff82a69","observation_id":"ce92016d-7ea4-4ded-8015-930fef555931","resolution":{"observed_at":"2026-05-26T13:17:49.514644Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Shielded diffusion: Generating novel and diverse images using sparse repellency","venue":null,"work_id":"0f6cfbeb-a02b-4094-9dd2-7964a577eb68","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:04107e028be028ea30a347c8bcc473008a5d27720db4d27ba380364f3461193c","observation_id":"c14ea867-ad5c-42f5-b994-44ca9fa98be7","resolution":{"observed_at":"2026-05-26T13:17:49.461459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Feedback guidance of diffusion models","venue":null,"work_id":"f6da7564-cc06-4b23-a1c6-bd7840a81db9","year":2026},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:0cc74308a9f3118107623b1c083895076fee193948a2ccadb5b0b9d73ec33b3a","observation_id":"2bf8ade4-a2e2-485c-bace-387436f54df4","resolution":{"observed_at":"2026-05-26T13:17:49.570244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Applying guidance in a limited interval improves sample and distribution quality in diffusion models.Advances in Neural Information Processing Systems, 37:122458–122483","venue":null,"work_id":"4d024f46-f68f-4d39-bbf6-70804005dc8f","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:b1f4941b979d134a726033a19e58718c7ffc3b01c1c759e0adf8ca41a3bdd92f","observation_id":"924a9cda-d3c8-4a4f-a549-b8eb5f2bc75f","resolution":{"observed_at":"2026-05-26T13:17:49.485128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Laion-aesthetics predictor v2","venue":null,"work_id":"0c98f6bb-a46e-41ce-a19f-eafc855786db","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:ddee08e38703c8df9a681a1c530efe02dba4ac919f25a0f33db713b2a33bac1c","observation_id":"dc6ce5eb-8e8d-4a35-b93e-ba7b672aa5d1","resolution":{"observed_at":"2026-05-26T13:17:49.529059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Diffusion-LM improves controllable text generation.Advances in neural information processing systems, 35:4328–4343","venue":null,"work_id":"18f7da46-476a-4b13-be27-1fd073c8f08d","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:adab6fee7cd79a73ad9c8f9364779c4149f7fa5b79c734ebf86cfee5a448f152","observation_id":"383634c4-10f8-4c6d-88db-590d3a08c9c6","resolution":{"observed_at":"2026-05-26T13:17:49.448471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Microsoft COCO: Common objects in context","venue":null,"work_id":"f9d2909a-8c01-4f7a-baa5-57b89b876689","year":2014},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:cdcdb80b21a57ef19f9efa33c2f76be669a22beafbcd9c17a48c95910daae635","observation_id":"8a9a9324-fff0-4b13-9eaa-30bb19360c85","resolution":{"observed_at":"2026-05-26T13:17:49.450244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"883187a8-4b13-4a7f-9c03-32fa967b4e11","year":2023},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:a6b80ee2d1cc932100d5d77a11bc23e2a824417e8dd403d8ef588147a44291d3","observation_id":"dbd1362d-04fb-4e36-a3c4-376678f371ba","resolution":{"observed_at":"2026-05-26T13:17:49.481804Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Flow straight and fast: Learning to generate and transfer data with rectified flow","venue":null,"work_id":"2c157360-0dc1-4315-8367-6fad262e21af","year":2023},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:2491a77a6f295b21bb657d202dde430d74bf0c790f54a414e4e41636a32045d0","observation_id":"9b5eb67b-be0a-4717-a448-48046e213906","resolution":{"observed_at":"2026-05-26T13:17:49.464968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.17812","last_updated":"2026-07-05T08:08:32Z","snapshot_observed_at":"2026-08-05T02:04:40.290367Z","submitted_at":"2025-11-21T22:05:56Z","title":"Score-Regularized Joint Sampling with Importance Weights for Flow Matching","version":3},"cited_work":{"arxiv_id":"2511.17812","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2511.17812","snapshot_observed_at":"2026-07-07T03:18:10.688058Z","title":"Importance-weighted non-IID sampling for flow matching models","venue":null,"work_id":"8f5d7116-4a6c-4d9e-a64b-83e0c74ca50c","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"cited_paper":"/paper/2511.17812","citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:cc89914a189ad9c62922f01893f8e8e36dece1b4b51a70eebcd395ce5a3dbdfd","observation_id":"0e4aa639-949c-41b5-a764-5438ff611700","resolution":{"observed_at":"2026-07-07T03:18:10.688058Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Discrete diffusion modeling by estimating the ratios of the data distribution","venue":null,"work_id":"5c925007-7e9c-4667-8e0f-7a6243200ee4","year":null},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:7c3cedeea280138a7f20ff678f0d2495516759c3a1ebd6bd9ef3d7c850c459bf","observation_id":"f9a719dd-b39f-46d8-a7f8-f95a9e7c18ba","resolution":{"observed_at":"2026-05-26T13:17:49.529799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"2937af6d-c8be-4c67-bb30-cb597bf96239","year":null},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:56565cbc48a3348c9688b16d878476574bbf0dc7219a30908e78e5f0b31124f6","observation_id":"c5033e4b-c2b2-4788-8a5d-efd0578de277","resolution":{"observed_at":"2026-05-26T13:17:49.563387Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"ProCreate, don’t reproduce! propulsive energy diffusion for creative generation","venue":null,"work_id":"89873d3f-29c8-477f-b127-52c63c13526e","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:db419c8e0d1006907dde761806d24d098ebf01754db2aea5557a6d644fac670c","observation_id":"8dcf6799-1b44-4807-be4b-2dca44fda744","resolution":{"observed_at":"2026-05-26T13:17:49.493831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"DiverseFlow: Sample-efficient diverse mode coverage in flows","venue":null,"work_id":"a5924ccc-1482-42a7-9345-d42d37e3c645","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:5cfabbef8c035ab76a2a86683cf9fe91b373d7c71dc9847074dd1ffeb27d5fdc","observation_id":"a2000be2-3789-4643-a814-f97b8ada5849","resolution":{"observed_at":"2026-05-26T13:17:49.548578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1090/s0025-5718-1994-1254147-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Narcowich and Joseph D","venue":"Mathematics of Computation","work_id":"edd65e21-9e44-4402-b64b-3078ab3bfe18","year":1994},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:97837960c3d476b85dbb0fdc63fe927af95be6c25748b224d8f22903118d91ba","observation_id":"2f026a3e-d779-461f-a91a-b9dc78399822","resolution":{"observed_at":"2026-05-08T21:39:15.300324Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-07-11T00:19:02.474592+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T00:19:02.474592+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Representing flow fields with divergence-free kernels for reconstruction.Proceedings of the ACM on Computer Graphics and Interactive Techniques, 8(4):1–21","venue":null,"work_id":"cc63eddb-c22d-418d-a9dc-f516ec2c7e2b","year":2025},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:a09febbe95de888ef8b1b46e3e1c0a15c81f70d31ea5bc95c2c2c53f89ef4ad7","observation_id":"cea16668-34d2-4442-a683-6c72bc6fdc85","resolution":{"observed_at":"2026-05-26T13:17:49.540296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-07-06T06:49:24.960992Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":"1807.03748","doi":"10.1609/aaai.v36i10.21390","metadata_source":"pith","pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Representation Learning with Contrastive Predictive Coding","venue":"cs.LG","work_id":"7b08a1d4-d565-424e-9c86-6ef244b7b90a","year":2018},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:0ba5c6b8d16e6a1f3b92a335e1db0c30c7fa0a6462f8905608b0c5f70c5b5201","observation_id":"7dd7db10-653d-4e10-8b91-d8da4c59f3dd","resolution":{"observed_at":"2026-05-11T19:16:07.366309Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Inequalities for differential and integral equations","venue":null,"work_id":"09aedfb2-ef09-4184-9e85-c3a5815fa804","year":1998},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:3f5786a5f8bbfb1018b3357de714ced5ca118d20faff8c46039a6f96d0f58cf6","observation_id":"4ffa6def-d012-4e7e-8257-bcd1372fc9ce","resolution":{"observed_at":"2026-05-26T13:17:49.432188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Scaling group inference for diverse and high-quality generation","venue":null,"work_id":"7360e410-e7aa-413f-8e1e-97966f6fdc77","year":2026},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:5654f3ae300ba9e401a2a544342a4fecedbae0844bce1787368b7b89ad383e21","observation_id":"74660522-67a3-4e29-8065-b960c324218b","resolution":{"observed_at":"2026-05-26T13:17:49.522673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"SDXL: Improving latent diffusion models for high-resolution image synthesis","venue":null,"work_id":"9996e576-0b5b-4426-b072-a7a5a8556dab","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:16dc4caa088b95ca957f5ede153d77fa6b38b998c5145e7bda6ea63cdeaa16c8","observation_id":"a9547ca2-3550-41d8-a5e1-e8075f9751ae","resolution":{"observed_at":"2026-05-26T13:17:49.457304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-07-09T07:16:04.687562Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"ad3e05b3-af3a-4fa2-ab30-c45f9f403277","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:34f5964f0d3a43508f52ae1dfe48d82e89174cec002d681ebc5fb269e085f030","observation_id":"ae7fa3d9-3760-477a-89cc-d6a81b7e93cc","resolution":{"observed_at":"2026-05-26T13:17:49.469903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"c5121414-118d-4ac5-abbe-0706b781627f","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:4bcf09eee5b5ac8de48ab65216aded95e7ea31786f3b844165a0d34d4b57e035","observation_id":"b0c05e5d-903a-49ac-9f93-5dc3340a78ac","resolution":{"observed_at":"2026-05-26T13:17:49.545332Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-07-11T02:27:52.409989Z","title":"High- resolution image synthesis with latent diffusion models","venue":null,"work_id":"5427867b-47ba-4d43-a415-2912684a2d41","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:c52a33aac9cd4263e9ca0e8887d18fe3059eb67196c51576b278b7b597d4e802","observation_id":"89f096f5-87d9-46cf-96e5-42b26f398659","resolution":{"observed_at":"2026-05-26T13:17:49.551698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"7c9568e1-0f4c-4cc6-bba1-25a6baf99e0f","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:5deb849f59b96f79206e1201228c5abcfaecb38f852554d3da600d285fa9754e","observation_id":"e84d2b52-0d78-4e1c-adf0-b5fd3b6ec47d","resolution":{"observed_at":"2026-05-26T13:17:49.554385Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Simple and effective masked diffusion language models.Advances in Neural Information Processing Systems, 37:130136–130184","venue":null,"work_id":"70a87109-83e1-4b39-a866-217c0a538cdd","year":2024},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:3f3b472e52ce83b4eb94fea6e538f2d936c96e8044d306ff0a3acf7bf47bfeb6","observation_id":"cefca909-d681-4126-b8ee-828153fcab87","resolution":{"observed_at":"2026-05-26T13:17:49.560105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-07-10T11:37:04.026195Z","title":"Deep unsuper- vised learning using nonequilibrium thermodynamics","venue":null,"work_id":"ce0dfb73-bf9c-46e7-81a3-f1f2862cf504","year":2015},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:c2dc65f0faa39b1881cb723bc3e6b4eac08e28b32495d3f97d823559b46f7a29","observation_id":"a648fb18-a3a4-4b6a-bd92-0c8015ae8702","resolution":{"observed_at":"2026-05-26T13:17:49.566967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Denoising diffusion implicit models","venue":null,"work_id":"1b6a2180-1185-4a85-aa20-d11bdb3b9450","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:f9d5212498b3d749e756ee82600e49fc301e63fe1a9bd62e58245203c1c7c6e9","observation_id":"03ca509d-a330-4700-8cb0-fcb1b8d5174b","resolution":{"observed_at":"2026-05-26T13:17:49.542124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole","venue":null,"work_id":"1a3961be-8309-4702-97ce-218446ab02d6","year":2021},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:333e67e37fd3550ae69695a0f7f5010f60049afd27bcb9a5309c0197bdf4e013","observation_id":"4edb5c9a-9743-47dd-8e28-f86d923e2fca","resolution":{"observed_at":"2026-05-26T13:17:49.532214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"A bound for the error in the normal approximation to the distribution of a sum of dependent random variables","venue":null,"work_id":"6b2edc4b-2da9-42b2-a469-d517851aa841","year":1972},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:45fa5fe737fddf28500360d76ea3973d3e72582577e5699ac4f53883efd2d88d","observation_id":"96b04749-8650-4dac-9c7e-cbce6772af83","resolution":{"observed_at":"2026-05-26T13:17:49.535493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-06-05T21:23:00.469572Z","title":"GeoDiff: A geometric diffusion model for molecular conformation generation","venue":null,"work_id":"a718b380-87d6-4c91-8cc3-dfc52a9de288","year":2022},"citing_paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-08T12:29:16.215618Z"},"links":{"citing_paper":"/paper/2605.06553"},"observation_digest":"sha256:b64252bc61a048d5be3bbb6ad695134d438244415a45f2d4d07cb75c217ab9d6","observation_id":"524a4381-67da-4193-9279-6b028a2bfa2a","resolution":{"observed_at":"2026-05-26T13:17:49.538917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.06553","last_updated":"2026-05-07T16:49:12Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T23:19:00.794334Z","submitted_at":"2026-05-07T16:49:12Z","title":"Diverse Sampling in Diffusion Models with Marginal Preserving Particle Guidance"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":5,"verified_exact":5,"verified_fuzzy":39},"total_outbound_references":51},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2605.06553."}