{"as_of":"2026-08-19T07:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de604736b5718b49614e78e5f0d06f0c72de49c71db62d98cf174fd3109fed90","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T04:58:24.486250Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2606.29665/citation-record","integrity":"/paper/2606.29665/integrity","json":"/paper/2606.29665/citation-record.json","paper":"/paper/2606.29665"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T04:58:24.486250Z","title":"Sliced and radon wasserstein barycenters of measures, 01 2014","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:08307356f628b238088c29e46595ed9dbe26e5af4ef6627993c38b2c75823ca9","observation_id":"ac942060-777b-4db4-ae65-8a534bfe0729","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:ecf076bdca3c79833c349afc9ea2e85d20ee02db2a250815435523d9b3a73a88","observation_id":"5f8bf41c-53af-4842-9700-b7490c4c3f29","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Sliced iterative normalizing flows","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:4eead0d7d31cfe5f4b4c20aa37f380870bebb2390d654b3f4bfff56682f3af3c","observation_id":"10d0f955-dd97-4f72-82dc-52fdaca39d0f","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:3e91381353cfc96604bb1c68bd235e12a39fc2c993a77e11c9abfb859a55f2ef","observation_id":"e462caec-34d5-4d96-9dda-65373d1c3f15","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":null,"venue":null,"work_id":null,"year":1968},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:31c7f53525807c31ecb1464f546c34d12bb5b53c6489535c514bfc9835281823","observation_id":"79ddfff8-8d19-4ec5-a7de-f45c4259aaa2","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"On the rate of convergence in Wasserstein distance of the empirical measure.Probab","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:e5adb3a04494b37b0fdcfece65925655211342e8d9d289ebbc60f6a7d8af4ff3","observation_id":"c6dad5c6-721c-49e6-9f2a-7fb737214531","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Generalized sliced wasserstein distances.Advances in neural information processing systems, 32, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:d7a2475ef7c0d5e9bae6e99f8d1438cd4d2221604a470d01b5ba4fb1a08bda52","observation_id":"9fb05e71-4c83-4a42-9fe7-793a71d931bb","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Projection robust wasser- stein distance and riemannian optimization","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:498fa69ff1c248f318cf2343712c513fa8c37ee19d39b5a86b1482ac53d596f6","observation_id":"6ff86ce4-90a0-40a5-bc34-61ba16f01cd6","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"On projection robust optimal transport: Sample complexity and model misspecification","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:2f24a05e712656892d73814277f6624f84c1be2d1aff331ea85fc93fe859243d","observation_id":"d07f5c7a-6617-4d4d-9c93-446f354b568e","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:ed68236b30b53bbcf8e50f932573cd8b5107e244fd78ac99c26781dec41e0f88","observation_id":"2fc0c286-68fb-4f71-9b75-d2fcefa1a80b","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Energy-based sliced wasserstein distance","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:67786d4c5677295f81f7a3ef7d253c379131149b866f5f18b5236f07e34a5d62","observation_id":"3e3c0c60-f3e0-4c8f-a59d-d8ef785b0370","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Distributional sliced-wasserstein and applications to generative modeling","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:cb799aa541dc9bf0f39108de0d720e945bd003c5d11f4ce4c41bc5889338be68","observation_id":"e6145f09-e68b-42b2-b51a-9886dee0af84","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Markovian sliced wasserstein distances: Beyond indepen- dent projections","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:0100204276b426ac00173a5929ffe904850108ddd6e0a893c314113df77a8c11","observation_id":"ba2a91fc-d0a2-4c6a-a2ef-4b8502826e0b","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.13570","last_updated":"2023-02-06T15:38:47Z","snapshot_observed_at":"2026-08-18T15:44:51.492024Z","submitted_at":"2022-09-27T17:46:15Z","title":"Hierarchical Sliced Wasserstein Distance","version":5},"cited_work":{"arxiv_id":"2209.13570","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.13570","snapshot_observed_at":"2026-06-30T05:04:20.475710Z","title":"Hierarchical sliced wasserstein dis- tance","venue":null,"work_id":"1b753c96-a59a-4d38-bb95-7c2594d9d0f5","year":2022},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"cited_paper":"/paper/2209.13570","citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:a205f62038bf41c587a1ee34a2e0eeb0bc34ba0cac688daf904555df62d4dd78","observation_id":"625baf11-d25c-47cb-b03f-d35295e1df76","resolution":{"observed_at":"2026-06-30T05:04:20.477846Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-06-30T04:58:24.486250Z","title":"Statistical robustness, consistency, and computation of sliced wasserstein distances","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:ca0eaa2ecf23422c40e73885199494836cc6117483193fe5a72eeebe9fc9c41e","observation_id":"7f7cbbaa-df88-43c0-b433-9dccca103dc1","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Subspace robust wasserstein distances","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:1e6656118efe1b3e3ce75663f0be8b31a55a5d709227a849daf5f64bb166d0f3","observation_id":"465cba0f-dd76-452e-a2bc-5b01715ec79b","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Wasserstein barycenter and its application to texture mixing","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:248fdde536944918dbda972c50e27533db96e222d16cc98753a4289ea7c41cde","observation_id":"14254308-cc8a-4627-b3ba-87ea0a899b03","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Optimal transport for applied mathematicians.Birk¨ auser, NY, 55(58-63):94, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:7addae3f391800dfe71dbbbcf5ac2353a58d5d072d13e59c5718fb2ea5425740","observation_id":"6540a1cd-28fb-4712-8c5b-1a40a9c6ce19","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Sutherland, Liang Xiong, Barnab´ as P´ oczos, and Jeff Schneider","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:ff2031a3b20afd7315e985cad20116508dc5ff9fbc3a384cd44ea73cff94a113","observation_id":"15c74038-1234-4471-bcb9-f34ba10aaf8c","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Hershey, and Soheil Kolouri","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:3af634f014470fed9bdf50fb586e4286887197380ce72c3a3e171128c42d6ff9","observation_id":"83c77101-2290-47fc-a680-7f7900d655a6","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:f2432ca6bb5e94374dd996614fb80fd79c246e086618a5717b1a09e8d01144e3","observation_id":"7d4d20f8-30df-4e82-aea6-28fdebce92f2","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","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":"2026-06-30T04:58:24.486250Z","title":"Springer-Verlag, Berlin, 2009","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-30T04:58:24.486250Z"},"links":{"citing_paper":"/paper/2606.29665"},"observation_digest":"sha256:c529160d6b1758422f51c5aed105dae133e5b4aef2ce66a2247e972fc08929c9","observation_id":"fb88e1bd-3a14-41ac-bf28-12f2cde03d27","resolution":{"observed_at":"2026-06-30T04:58:24.486250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.29665","last_updated":"2026-06-29T00:19:56Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-05T13:26:13.181916Z","submitted_at":"2026-06-29T00:19:56Z","title":"Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":22},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2606.29665."}