{"as_of":"2026-08-11T04:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:42ee9c94958ec82983ef85a7bb5716af2fdd309e90e6ce5efb7e313dd14dcc50","coverage":[{"denominator":70,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":70,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T04:37:15.159317Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-05-12T00:52:21.387658Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T08:41:23.816554Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"cited_work":{"arxiv_id":"2501.17770","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.17770","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2501.17770 (2025)","venue":null,"work_id":"f36fb296-5334-4592-8d0d-f0b84655b46c","year":2025},"citing_paper":{"arxiv_id":"2605.08424","last_updated":"2026-05-08T19:33:36Z","snapshot_observed_at":"2026-07-06T23:20:38.385189Z","submitted_at":"2026-05-08T19:33:36Z","title":"Generalized Wasserstein Flow Matching: Transport Plans, Everywhere, All at Once","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-12T00:52:21.387658Z"},"links":{"cited_paper":"/paper/2501.17770","citing_paper":"/paper/2605.08424"},"observation_digest":"sha256:7bee9f8e27932d21cf80b4d3eaea79481b41b3d65ebcab8d138454986ee519b6","observation_id":"024b00e9-0e4a-4414-8491-ab14bb2a94f4","resolution":{"observed_at":"2026-05-12T08:41:23.818569Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.17770/citation-record","integrity":"/paper/2501.17770/integrity","json":"/paper/2501.17770/citation-record.json","paper":"/paper/2501.17770"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.559568Z","title":null,"venue":null,"work_id":"5677a4d7-7314-4e8e-9435-60c01a891a34","year":1998},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.778098Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:319062360628e7815dd6c7bfcd185aeb1e72210317ae408da4be8bd9ad543db0","observation_id":"bfbea170-cf59-4e53-a6f4-eb8efc981989","resolution":{"observed_at":"2026-08-10T04:37:16.564793Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.542981Z","title":"The multivariate gaussian probability distribution","venue":null,"work_id":"7157ff9f-7081-42f2-964e-bc1ee0698551","year":2005},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.783566Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b554bf5e7f6cb210d7716a3127162fd59d52844eaeae1676918cb93fad600dc7","observation_id":"80ac39d2-89cd-4903-aa2f-a86f3a5e9420","resolution":{"observed_at":"2026-08-10T04:37:16.547999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.525964Z","title":null,"venue":null,"work_id":"28ae8dad-ba11-473b-863a-13b55ab7d9ff","year":2003},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.788726Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f2c2e535179069cad8d1f85956c9e696d2e12efaa0c1c30383a34e9d70a01bce","observation_id":"c12e6d7e-1c9f-423c-ab5a-4df5e701c168","resolution":{"observed_at":"2026-08-10T04:37:16.532255Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.794555Z","title":"Single-pass streaming algorithms for correlation clustering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.794555Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:e3c146733709d2f687fd782f982583e421ed002f86428c9c77ad2cd6e75ba05d","observation_id":"4191c067-e8f5-4657-86ea-43be496362d4","resolution":{"observed_at":"2026-08-10T04:37:14.794555Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.496663Z","title":null,"venue":null,"work_id":"cbe79298-0cfe-4169-8814-d97c294b7ea6","year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.799938Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:5f2c7bed1ea4f696e69da023d3d636e1ebfac01f1c6eed24780aee8be7ab1370","observation_id":"a32dd2d7-ae0d-433f-ac4b-ead2470fcb7d","resolution":{"observed_at":"2026-08-10T04:37:16.501636Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.479980Z","title":"Modeling temporal data as continuous functions with stochastic process diffusion","venue":null,"work_id":"66a26fa1-772c-4eaa-b9ec-c22e1288ee7f","year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.805419Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f39cd3db42e70eafddfab551f4b7a89cf62380969eee04560002beb036555c5f","observation_id":"46db6656-48c6-4b7f-967d-44c98247177f","resolution":{"observed_at":"2026-08-10T04:37:16.485402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.812480Z","title":"T., Rubanova, Y., Bettencourt, J., and Duvenaud, D","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.812480Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:a42ef04f67ab809ae99acbefb3497a8eeedabfa9fa39ee56477f7d4c14e8673a","observation_id":"cae232d3-8d01-4172-abff-d7c0315a26bc","resolution":{"observed_at":"2026-08-10T04:37:14.812480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.450575Z","title":null,"venue":null,"work_id":"4ff4998d-f4c7-40cd-aa90-89ebcad0cb14","year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.818463Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:7148556416b647b3be229dce07f3f12b2941504231db8feb70d3732d0f4b206f","observation_id":"d0d9ce59-ef56-4a1e-b6b1-60191cce23f6","resolution":{"observed_at":"2026-08-10T04:37:16.456218Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.432363Z","title":"and Zhou, M","venue":null,"work_id":"8135edf7-36d7-4c17-b7cf-d03c03fa4454","year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.824282Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:64a51315f7943fff9ccd5b49f0d175483b151a938546f6f94c32bba3892a8473","observation_id":"3191304a-e04d-41f9-afb4-f2a8338a9389","resolution":{"observed_at":"2026-08-10T04:37:16.437664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.414572Z","title":"System Data - Citi Bike Trip Histories , 2024","venue":null,"work_id":"73d4b3a8-643c-4eda-a42c-354504cbb6ba","year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.829584Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:01e6096c24bff28a388009130924baca0c405812a82d83287a66fc91a3b05b0a","observation_id":"600800ad-9db6-4976-89d1-885569b0511c","resolution":{"observed_at":"2026-08-10T04:37:16.420226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.392151Z","title":"and Kalmykov, Y","venue":null,"work_id":"26d90a35-b5ae-4baf-a680-9624a44a5bfc","year":2012},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.835129Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b3d17a0c442f0c89e3934babfee965628e633d96c794bcb2fd6c8be77ce94d90","observation_id":"6194f4db-269c-47e9-81bf-c62d8adcb4d7","resolution":{"observed_at":"2026-08-10T04:37:16.398241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.375873Z","title":"and Isham, V","venue":null,"work_id":"43197cb7-f5ad-48c5-9cf8-dfc8bbf35105","year":1980},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.843983Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b9c3ed7a1fa0b97b9f29cd0272aff04d19c5716e70f894b4ce4efdaae1aee4b3","observation_id":"dd7464d6-7fc6-4653-8111-b2565617bbb9","resolution":{"observed_at":"2026-08-10T04:37:16.381469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.356094Z","title":null,"venue":null,"work_id":"508c304e-4fce-4419-99cf-e49747da5449","year":1955},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.849320Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:26b7db0a7d77e1a0aeef97e1210b08747419e5246855f11c3131e2cabe7fa085","observation_id":"be35c937-985e-4361-9449-38dc52002cb8","resolution":{"observed_at":"2026-08-10T04:37:16.361401Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.854462Z","title":"and Nichol, A","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.854462Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f43ef6af53dac795e5992b587efd722c65aacfd165084a7bbe98cb14f6b70294","observation_id":"2e46ceab-a3b6-494a-a8ef-944cde7bcc49","resolution":{"observed_at":"2026-08-10T04:37:14.854462Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.323367Z","title":"M., Kotecha, J","venue":null,"work_id":"5c64ab0a-7a3a-4a44-9327-7bf6297d053b","year":2003},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.859230Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:cd7fa3f130e4e6c5e0fc3ea8336ad30e9bb19eeb464111f42cdb44292d581ef7","observation_id":"7b8124f1-7f9d-46ba-8df8-38834beaf616","resolution":{"observed_at":"2026-08-10T04:37:16.329300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.303186Z","title":"Recurrent marked temporal point processes: Embedding event history to vector","venue":null,"work_id":"930e52bc-1adf-48ca-a7b7-0c90c921263e","year":2016},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.864279Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:a107e7974b1860ca46d8102a6151eeb2ca83dd34bbfa92e73329f7b301a347db","observation_id":"a04d5ef1-f5d1-49e6-a288-150fa8e73143","resolution":{"observed_at":"2026-08-10T04:37:16.309347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.285503Z","title":"and Joshi, M","venue":null,"work_id":"92d1a538-d007-4295-8bc0-55df0beca0d3","year":1998},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.869061Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:5646adccf2594f65c00a99b6d25c539d23681c2a40197d4014a43c735d03ac46","observation_id":"ba1b2300-1004-42f9-b8e9-822bb3cbfde9","resolution":{"observed_at":"2026-08-10T04:37:16.290445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.874382Z","title":"D., Murphy, K","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.874382Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:011200fd3a7e9e86232acff7be97030b417471f85608b7aa42b365816f00e4a6","observation_id":"8985b576-92cd-46de-90a4-85a85730c8c6","resolution":{"observed_at":"2026-08-10T04:37:14.874382Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.879387Z","title":"Generative adversarial networks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.879387Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b685b52d47e445c460fc4212e32871ccfd93c7ce8967e8074ab88fba84e0676f","observation_id":"c8cd605f-1f48-46a3-9eb0-487505491069","resolution":{"observed_at":"2026-08-10T04:37:14.879387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.245401Z","title":"and Graves, A","venue":null,"work_id":"2a2ef0f9-35ec-4932-a48f-aa48598f9e33","year":2012},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.886109Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:63c4ebb08c9e9b041a6b974184761c65afacd2d602e0daa3451a002d56b3757a","observation_id":"6739ddd4-80fb-435b-a1dd-4f6081a61033","resolution":{"observed_at":"2026-08-10T04:37:16.252851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.891177Z","title":"M., Rasch, M","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.891177Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:bcf11c2586feed224bfc0a1cf86b0d796e736caf2037b02b7c78d42a5e36c895","observation_id":"5a17be35-4ae1-48df-8eba-bbefc27b1270","resolution":{"observed_at":"2026-08-10T04:37:14.891177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.898020Z","title":"Lafma: A latent flow matching model for text-to-audio generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.898020Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:0d697dac6a0ac085ae343f802bd47f7c65fdcc1c68d709a9f18f37a8f015a956","observation_id":"31a6c817-3e06-48a9-b61b-5bbb8b2f043f","resolution":{"observed_at":"2026-08-10T04:37:14.898020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.904149Z","title":null,"venue":null,"work_id":null,"year":1971},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.904149Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:644d5211af40123f2ed855832590b6659db32b7bd85d8d5cdba0c7fcff1f4b21","observation_id":"a1ce137e-0dd4-4ccf-a893-8d7bc736364a","resolution":{"observed_at":"2026-08-10T04:37:14.904149Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.909747Z","title":"Denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.909747Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f158cfe2938666259c5a82e7f2d12e996b06ae0cb3b71f4603b1ccc2745ef44c","observation_id":"b41ca6f9-9975-4eaf-aa6c-11dd0c75147f","resolution":{"observed_at":"2026-08-10T04:37:14.909747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.914769Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.914769Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:4bea9a3bb5b14a2013e604cbddebc853cdcfa9857d6ff752590c68759efe0daa","observation_id":"acd65ae4-6718-40e4-884d-f93d822a15cf","resolution":{"observed_at":"2026-08-10T04:37:14.914769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.166191Z","title":"Generating and imputing tabular data via diffusion and flow-based gradient-boosted trees","venue":null,"work_id":"7af6894b-a512-4d2e-b374-5a59b4d606b9","year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.919973Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:cdb44d4fa32f03eb5684018deb6f1f8786d92bbb433d54b8e96994db7ff703d5","observation_id":"4df627db-914e-4d34-b9c6-229cfa08744b","resolution":{"observed_at":"2026-08-10T04:37:16.172104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.146478Z","title":null,"venue":null,"work_id":"ee3219c7-9ccc-4f74-95db-488e9dc558b0","year":2014},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.925905Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:4514f7fee918dacab86b9be70205381afb340aae4a54a96659c8980db58ab8ef","observation_id":"c191b6f7-c4f0-4e1e-92d8-b00b2bebe74b","resolution":{"observed_at":"2026-08-10T04:37:16.152825Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.126051Z","title":"Functional flow matching","venue":null,"work_id":"456f7149-4f3a-45e2-b3f4-4c0294422a9b","year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.931006Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:4d5e45daf29d3cbd98bac8e3d9aac9510e06b194e44684d838d7907f0ba523b8","observation_id":"acd589ae-5acf-4c46-a512-2289749a2cfc","resolution":{"observed_at":"2026-08-10T04:37:16.134502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.936093Z","title":"Neural controlled differential equations for irregular time series","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.936093Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:684d413a6539c643791f31cd26babd50e36f7d92bec05416e91fea0f5ac5b7b7","observation_id":"e4a05931-8180-416c-9a4f-afed55086e91","resolution":{"observed_at":"2026-08-10T04:37:14.936093Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.940933Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.940933Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:0d204e267c442d0b0e720fa5a32811346a2f0ba1b20e027d78a5dd8c58f45434","observation_id":"8e43b511-53fb-445a-bf60-6b5435f3e064","resolution":{"observed_at":"2026-08-10T04:37:14.940933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.080088Z","title":null,"venue":null,"work_id":"6c203e05-cd22-4e62-aec1-bedf56298f04","year":1992},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.945555Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:fa0dfb812d36733f92edae0999cd8949cab723e3b62ddf5d16058a3547e838f5","observation_id":"6ac73f1a-e1ae-409e-8283-6dde097925e3","resolution":{"observed_at":"2026-08-10T04:37:16.085314Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.950845Z","title":"Tabddpm: Modelling tabular data with diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.950845Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:dbd7b2e6bfa7eea8b17917978422e8b7f4e2ec81266573790a553025b977a220","observation_id":"a58f0e82-3a9e-4353-84b9-980f56df2ea9","resolution":{"observed_at":"2026-08-10T04:37:14.950845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.051809Z","title":"Gaussian measures in banach spaces","venue":null,"work_id":"4d0d7869-ef79-4c37-a987-628046db9571","year":2006},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.955490Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:ba78ae62b40dfc661ee86c1b81aebcd3d5360bb5801caa78ca5619cb7c0f8315","observation_id":"4861eb87-1bc7-4548-91ab-5ba76be69247","resolution":{"observed_at":"2026-08-10T04:37:16.057178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.960702Z","title":"A tutorial on energy-based learning","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.960702Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:7daabd952a66348a900537ed95f0e4a93dda844c5a5fb620153b1892a6c97f20","observation_id":"81b20f28-9cdd-4938-8fe6-b6dd278b7b10","resolution":{"observed_at":"2026-08-10T04:37:14.960702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:14.965470Z","title":"S., and Hashimoto, T","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.965470Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:25f1245047847f6903ee138f226f4b914d0ef6546b44402ea1cfdf95efe53346","observation_id":"04b96feb-3feb-40f4-bba0-a5350e9be55e","resolution":{"observed_at":"2026-08-10T04:37:14.965470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:16.001731Z","title":"B., Azizzadenesheli, K., liu, B., Bhattacharya, K., Stuart, A., and Anandkumar, A","venue":null,"work_id":"0f08ca4c-cddf-4205-98cf-d5730f4be473","year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.972267Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:699e24ddb93e78f098886c9eacb3af615f6b1826aeb30df120cc29193e5e42a0","observation_id":"0a041b3a-1ebe-4ab5-9f82-3246cfcd1b7c","resolution":{"observed_at":"2026-08-10T04:37:16.007438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.07400","last_updated":"2025-01-22T01:31:03Z","snapshot_observed_at":"2026-07-06T14:51:56.435442Z","submitted_at":"2023-02-14T23:50:53Z","title":"Score-based Diffusion Models in Function Space","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.07400","snapshot_observed_at":"2026-08-10T04:37:14.977456Z","title":"H., Kovachki, N","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.977456Z"},"links":{"cited_paper":"/paper/2302.07400","citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:7ee10a35b5b9040b500d5737190e6849a51c374e14dddc3996c3b7c3eef6b2a6","observation_id":"ce063187-a6f6-461f-85c9-83e385823164","resolution":{"observed_at":"2026-08-10T04:37:14.977456Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02747","last_updated":"2023-02-08T15:46:05Z","snapshot_observed_at":"2026-08-02T18:24:58.914589Z","submitted_at":"2022-10-06T08:32:20Z","title":"Flow Matching for Generative Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02747","snapshot_observed_at":"2026-08-10T04:37:14.983246Z","title":"T., Ben-Hamu, H., Nickel, M., and Le, M","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.983246Z"},"links":{"cited_paper":"/paper/2210.02747","citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:8594691772af52909dfe68db4917702dd097c61f34b3cc29aeba79953471a336","observation_id":"3b2f2300-d11c-4209-bc0e-d2dfafbf970c","resolution":{"observed_at":"2026-08-10T04:37:14.983246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.984854Z","title":"u dke, D., Bilo s , M., Shchur, O., Lienen, M., and G \\","venue":null,"work_id":"b7e0cb75-f1da-4287-a58b-966fce2c3c97","year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.990105Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:e2d98cde40c3838e28e3af8d4769417e6909cb306a548667b6ef99c3391ec31f","observation_id":"769bee61-81f1-45b5-ac6f-8d464e80ab02","resolution":{"observed_at":"2026-08-10T04:37:15.990139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22493","last_updated":"2024-10-29T19:33:18Z","snapshot_observed_at":"2026-08-04T23:39:29.669415Z","submitted_at":"2024-10-29T19:33:18Z","title":"Unlocking Point Processes through Point Set Diffusion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22493","snapshot_observed_at":"2026-08-10T04:37:14.995183Z","title":"u dke, D., Ravent \\'o s, E. R., Kollovieh, M., and G \\","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:14.995183Z"},"links":{"cited_paper":"/paper/2410.22493","citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:3eec414dbedc7c27a0739a86bda888b5aece9ad0597e44506a6cb7a1be5850d2","observation_id":"ad8d69e4-3eaa-4dd0-bc93-713e8d799f63","resolution":{"observed_at":"2026-08-10T04:37:14.995183Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.968913Z","title":"and Hu, W","venue":null,"work_id":"a9b5ebd6-8783-40ac-8f7a-de343a2b5751","year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.001034Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:925f1586b31418a4d4f5c4ef99fe52044c4d8da5a637274bc95a11e0ede3e5fd","observation_id":"4d0501f7-c084-4d76-a313-352961246d6f","resolution":{"observed_at":"2026-08-10T04:37:15.973660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.951271Z","title":"A conditional point diffusion-refinement paradigm for 3d point cloud completion","venue":null,"work_id":"23de72fc-b995-48db-8561-6c05a384c6b0","year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.007063Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:020523795e5ff7b610f8403b353772054280f900e71736de3d4833a7fe9d3b2b","observation_id":"4baa0609-6030-4fc4-8c0c-777ce8a3a82d","resolution":{"observed_at":"2026-08-10T04:37:15.957251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.933537Z","title":"Pu-flow: A point cloud upsampling network with normalizing flows","venue":null,"work_id":"a3b4c991-ee92-4f23-bc19-cf84a14870d6","year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.015195Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:2d72e613662f1471151d81b23f15fc833ec5d62fa373dd339cdc529c2608d1c8","observation_id":"4b90dca9-fdc7-4902-8253-9940e30e8a4d","resolution":{"observed_at":"2026-08-10T04:37:15.939077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.915398Z","title":"and Eisner, J","venue":null,"work_id":"49d594fd-ce9a-4094-b489-54b901aec042","year":2017},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.021817Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:8cca134c96e377d881a74e32fa67dc41132af2552b8012ad9f6c06572a7ae3b1","observation_id":"67786e34-c035-458b-854d-7afc81b2b7d2","resolution":{"observed_at":"2026-08-10T04:37:15.920947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.894035Z","title":"R., and Waagepetersen, R","venue":null,"work_id":"edb71e50-3fd7-4acd-9de3-70d2c8d3a4e5","year":1998},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.028388Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:ae8d3a7c8a4b51e2e6bc93fb3004b044556fbb6865d7645d99a63885efa473ff","observation_id":"785c19d9-f78a-4aad-8c12-48b41e4cd671","resolution":{"observed_at":"2026-08-10T04:37:15.902363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.874767Z","title":"Gsd: View-guided gaussian splatting diffusion for 3d reconstruction","venue":null,"work_id":"59ececfb-9056-4035-a4dc-b8c6c7212862","year":2025},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.035091Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:c867de6513a6064c075a5815e21fc74ebc901a7367f885357544a4ccb43aba01","observation_id":"01acbad0-0ff8-4f51-97dd-bac93ce52bc5","resolution":{"observed_at":"2026-08-10T04:37:15.880737Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.854658Z","title":"Space-time point-process models for earthquake occurrences","venue":null,"work_id":"e0a6363c-8b24-41f8-a2bc-6f3e13621f12","year":1998},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.041549Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:4b6cedbb370ad7b1d4777d3360693996ae9b3d3b671dfa71560aae65eeac52c6","observation_id":"b9f6dacb-8350-4378-8753-16de75f6981a","resolution":{"observed_at":"2026-08-10T04:37:15.861931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.834066Z","title":"Deep mixture point processes: Spatio-temporal event prediction with rich contextual information","venue":null,"work_id":"3fc7a8d1-8a6d-46cf-afbf-f4c3849d5917","year":2019},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.047173Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:1bfc2fcc1b0ebe45683ca21c7309fba0ee2f21bd0857e634b26ffae29cfae724","observation_id":"e1d380e9-a2a4-4f06-b6ea-7065a40f284b","resolution":{"observed_at":"2026-08-10T04:37:15.841513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.812863Z","title":"Fully neural network based model for general temporal point processes","venue":null,"work_id":"2cb738cc-9af8-425a-8fa9-54e767107d29","year":2019},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.052288Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:df6a3209abe99e660a7131ba92ee3339616579d83722418e2abc27ab6dc4b107","observation_id":"9f4dbb23-d7a3-4384-add4-da93a8036716","resolution":{"observed_at":"2026-08-10T04:37:15.820579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"0941.29095","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.400409Z","title":"On-line new event detection using single pass clustering","venue":null,"work_id":"5f23f51d-10d1-4f65-8c83-c3d591171325","year":1998},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.057656Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f0f1e9a76b492a9bed0226c3be7d9ec18e6e83bab34d0c251a3428360f084260","observation_id":"bf7095c8-abd7-45c0-8b22-9db0a156a828","resolution":{"observed_at":"2026-08-10T04:37:15.411938Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.10130","last_updated":"2025-06-06T08:46:30Z","snapshot_observed_at":"2026-08-11T00:51:34.920506Z","submitted_at":"2023-02-20T18:00:38Z","title":"Infinite-Dimensional Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.10130","snapshot_observed_at":"2026-08-10T04:37:15.062622Z","title":"Infinite-dimensional diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.062622Z"},"links":{"cited_paper":"/paper/2302.10130","citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:afbccc1e0187c804bd323c3fc0b8cbebcc60a4c651693a5016d369a4f3471123","observation_id":"79f98e69-b5b5-41e7-9b14-f48494e8de7e","resolution":{"observed_at":"2026-08-10T04:37:15.062622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.791875Z","title":"On wasserstein two-sample testing and related families of nonparametric tests","venue":null,"work_id":"f0f4e321-ed6a-407f-8a5f-5daffba46978","year":2017},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.068161Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:daabab6ac2978851b0c7be06a476d1cd9dc760b8b769dcf13ef5c8401cb62abd","observation_id":"6c80f31e-0684-4318-b26c-452cfaa7c562","resolution":{"observed_at":"2026-08-10T04:37:15.799279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.769686Z","title":"Intensity-free learning of temporal point processes","venue":null,"work_id":"9f470fc0-6319-410d-a80b-3996dea57620","year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.073094Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:38e30f4fcc2589892c0695d0b5d01ab5fadc31728fb5988ed1179f8e2e57ad59","observation_id":"a1fd6dfd-07b7-4c94-8119-f13ba243b16c","resolution":{"observed_at":"2026-08-10T04:37:15.776228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.752041Z","title":"Fast and flexible temporal point processes with triangular maps","venue":null,"work_id":"02945e46-f48b-4e44-b4c8-6e8bd7289444","year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.077700Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:02f9f3e73065de7c7113189f063dbafa56362369c34e5dfd11e417d3cf40071c","observation_id":"5520f58e-120c-4897-848a-6418b710194d","resolution":{"observed_at":"2026-08-10T04:37:15.757897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.082821Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.082821Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:3747ad663d245fc2e00168377f0e18867eace70f6706d1848cb7fb476b339334","observation_id":"4032f5cd-72d2-4f11-bd62-764eaf611c53","resolution":{"observed_at":"2026-08-10T04:37:15.082821Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.087413Z","title":"P., Kumar, A., Ermon, S., and Poole, B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.087413Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:2e6f48449f831c5d86713eefae487563e98968db66ecb704b35b8b65a0b4379e","observation_id":"b8a98f10-1c98-4294-a334-47ea2d1970ad","resolution":{"observed_at":"2026-08-10T04:37:15.087413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.705758Z","title":"Coronavirus (Covid-19) Data in the United States , 2020","venue":null,"work_id":"48288815-2261-4537-a291-79f9edb68c8a","year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.092157Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f28d5d8f12493fb742d8d9a92d213d819d73f761799f4dda97b99980467d719b","observation_id":"543b3100-7b12-4504-b395-2d158a4632b7","resolution":{"observed_at":"2026-08-10T04:37:15.712982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.01844","last_updated":"2016-04-24T20:03:35Z","snapshot_observed_at":"2026-08-03T03:39:35.954006Z","submitted_at":"2015-11-05T18:22:44Z","title":"A note on the evaluation of generative models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.01844","snapshot_observed_at":"2026-08-10T04:37:15.097280Z","title":"A note on the evaluation of generative models","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.097280Z"},"links":{"cited_paper":"/paper/1511.01844","citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b853d29a45d79c98f87ae73ae88ce616b665fbef12df6e216a1f383f1b8fb479","observation_id":"13049484-286b-4e68-b311-a82531aa0c25","resolution":{"observed_at":"2026-08-10T04:37:15.097280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.683420Z","title":"Geological Survey","venue":null,"work_id":"9991fa1b-b860-48d4-9c63-a48dab5edea9","year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.102375Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:f860a1f1e298c0bc724bc1fd4fe1a09de7da3a516ada5272b1cff5f78c5cd0d9","observation_id":"3c88781a-29d5-40cb-9d56-c8a75d073ee3","resolution":{"observed_at":"2026-08-10T04:37:15.688755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.107570Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.107570Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:b5a84991e4d7226d70d701bcfaa5c5577ab9f49994846a4ec6184256fa22420d","observation_id":"c8caf692-f94f-4d14-8f21-766d0a56a6bd","resolution":{"observed_at":"2026-08-10T04:37:15.107570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.651360Z","title":null,"venue":null,"work_id":"186d7526-f092-407e-b861-0f6cbe326756","year":1976},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.113127Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:22e0dc78a97b0ee0d4b6a98b79ffee8b9afbb12243849ccf113bc6d8f076fa86","observation_id":"1579a969-d671-4d82-9648-460b924a8a98","resolution":{"observed_at":"2026-08-10T04:37:15.657946Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.118374Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.118374Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:a7b266f013ca76e17b5d46075152de37a1c3a7a0bcc0f6ef42e8ee4427fc7fb5","observation_id":"2a47d994-83d8-4518-8231-315108ba54ea","resolution":{"observed_at":"2026-08-10T04:37:15.118374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.602571Z","title":null,"venue":null,"work_id":"27e5403b-5631-4a79-abf2-292bb889bb6b","year":2021},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.124816Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:fafe4cc0b169f9165c14ff5fe131786efdba1b13714772a51a91c0f50a4bc498","observation_id":"a48da519-47f0-4510-9b69-4929146d984f","resolution":{"observed_at":"2026-08-10T04:37:15.608177Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.581404Z","title":"Global convergence of langevin dynamics based algorithms for nonconvex optimization","venue":null,"work_id":"53d42c54-360d-46b3-83d5-57b2a19f3651","year":2018},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.130418Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:c12607c11eaa8ffad3609e3e034080013b5cbbf8589c154b7ef92273d56d6908","observation_id":"98af0267-bfa6-4e0c-a1b0-f30f08301e03","resolution":{"observed_at":"2026-08-10T04:37:15.588587Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.135873Z","title":"Pointflow: 3d point cloud generation with continuous normalizing flows","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.135873Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:cced033b932bedb2ab7f9a8116cf3f900e7984106dc8a564cb52126c0f5b0613","observation_id":"d8680e61-5fef-4993-93a6-6b13e0a97ace","resolution":{"observed_at":"2026-08-10T04:37:15.135873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.548803Z","title":"Conditional gan for point cloud generation","venue":null,"work_id":"8b3918ab-1edb-42d0-b126-03dca3654fc7","year":2022},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.140768Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:46a87489b06fd7427556ef49dd80b0086344dab75e727828baf8b2d07b53151a","observation_id":"facc0e67-b970-4a28-befb-77be67079311","resolution":{"observed_at":"2026-08-10T04:37:15.554037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.528488Z","title":"Spatio-temporal diffusion point processes","venue":null,"work_id":"3d2713f0-17dc-4359-b8d0-aa46d192419a","year":2023},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.145315Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:8038ea38116cce91d86eecb2c09502e03fe59eb37fd9ca39e5619f2a3912d588","observation_id":"a32b42be-f435-4a8c-8b70-ff438dbc4e3c","resolution":{"observed_at":"2026-08-10T04:37:15.535348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.505781Z","title":"Self-attentive hawkes process","venue":null,"work_id":"c7de38a5-82b9-497b-8880-57ae7449f2e7","year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.150263Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:a10421d50599c188df62806c550df6bca526d80b7b73080c92962999fc4178f0","observation_id":"d4cec136-e24b-45b5-b288-b0030486d118","resolution":{"observed_at":"2026-08-10T04:37:15.511250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.154860Z","title":"Transformer hawkes process","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.154860Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:3b49e017e07b5375ef3c5eb06965c4eae4c0ef1bc1aacc112a1f306a32f88b6b","observation_id":"c9b9724b-35ef-435b-bf14-d9b4085d2ceb","resolution":{"observed_at":"2026-08-10T04:37:15.154860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:37:15.159317Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-10T04:37:15.159317Z"},"links":{"citing_paper":"/paper/2501.17770"},"observation_digest":"sha256:1109574fd6834a0ae7eb6642503fdf06b8c395c954cff7e2cd8f0a28b37384ae","observation_id":"62fdb92b-07e6-486a-9ae3-6509652a6b44","resolution":{"observed_at":"2026-08-10T04:37:15.159317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.17770","last_updated":"2025-06-03T22:37:00Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T04:30:25.794750Z","submitted_at":"2025-01-29T17:03:44Z","title":"Generative Unordered Flow for Set-Structured Data Generation"},"reference_resolution":{"displayed":70,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":36,"verified_exact":0,"verified_fuzzy":33},"total_outbound_references":70},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2501.17770."}