{"as_of":"2026-08-10T11:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:928f83c32b9265ad9a5c1e028e5652d882aff253c07892c8767f82b83d44e517","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":15,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T03:31:36.856353Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T22:57:26.202515Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2512.02826","last_updated":"2026-04-10T06:54:03Z","snapshot_observed_at":"2026-07-30T04:40:51.868176Z","submitted_at":"2025-12-02T14:34:10Z","title":"From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-17T02:26:03.356487Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2512.02826"},"observation_digest":"sha256:e49b3a90ee946470198d7c4e942f7f9b1ee613f2c1bf9f15ada71996011e844b","observation_id":"dfdd75d7-8656-411c-8391-e7dd46d6eed3","resolution":{"observed_at":"2026-05-17T02:28:53.340925Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2512.16768","last_updated":"2026-05-14T15:46:33Z","snapshot_observed_at":"2026-07-06T22:39:28.855621Z","submitted_at":"2025-12-18T17:02:11Z","title":"On The Hidden Biases of Flow Matching Samplers","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T21:10:19.571440Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2512.16768"},"observation_digest":"sha256:d11c0918a5ab76eda41ad719f3b8dd9b15c782b37d3428196687f3c167376288","observation_id":"8c8f6f37-d3a0-4595-8566-62a93818dec0","resolution":{"observed_at":"2026-05-16T21:11:16.961617Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-08-03T03:31:36.856353Z","title":"and Li, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.07928","last_updated":"2026-05-29T09:09:51Z","snapshot_observed_at":"2026-08-09T01:51:48.687831Z","submitted_at":"2026-02-08T11:51:50Z","title":"A Kinetic Energy Perspective of Flow Matching","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-03T03:31:36.856353Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2602.07928"},"observation_digest":"sha256:e91e7d90712c9db1c6c86bf348a5884b083301e1871a12f6ed5011567cf7c5b7","observation_id":"1e63b3ea-6b9a-4e81-8836-24e32ade9767","resolution":{"observed_at":"2026-08-03T03:31:36.856353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-08-02T21:26:58.817847Z","title":"How do flow matching mod- els memorize and generalize in sample data subspaces? arXiv preprint arXiv:2410.23594, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.20360","last_updated":"2026-06-28T22:31:13Z","snapshot_observed_at":"2026-08-03T22:05:49.929640Z","submitted_at":"2026-02-23T21:06:35Z","title":"Momentum Guidance: Plug-and-Play Guidance for Flow Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T21:26:58.817847Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2602.20360"},"observation_digest":"sha256:6049fb68c1f09b8328164f21fe49484febb0299d32c62063a65413ca426d6497","observation_id":"fb3c81ab-b41a-4494-8584-023ee571de97","resolution":{"observed_at":"2026-08-02T21:26:58.817847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2603.13419","last_updated":"2026-05-20T10:08:19Z","snapshot_observed_at":"2026-07-06T22:48:57.474272Z","submitted_at":"2026-03-12T21:02:17Z","title":"Diffusion Models Memorize in Training -- and Generalize in Inference","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-21T10:52:31.849094Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2603.13419"},"observation_digest":"sha256:be04beab40981dbfb1ad450101774cfe1bd51a1521f6a71d8dd20a744309583d","observation_id":"a1830376-886b-4c27-b137-3f7a53b8347e","resolution":{"observed_at":"2026-05-21T10:54:07.980923Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2604.16079","last_updated":"2026-04-21T08:05:28Z","snapshot_observed_at":"2026-08-05T07:26:53.340338Z","submitted_at":"2026-04-17T14:05:33Z","title":"The Amazing Stability of Flow Matching","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T08:37:37.238541Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2604.16079"},"observation_digest":"sha256:62ab80eea38f9edb8ab010dac692bf611db020afc6b3e4be699884103539d641","observation_id":"468dd830-a8b6-4405-92d2-cd270c17c874","resolution":{"observed_at":"2026-05-10T08:37:53.885482Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.08398","last_updated":"2026-05-29T19:06:27Z","snapshot_observed_at":"2026-08-02T09:24:57.733749Z","submitted_at":"2026-05-08T19:04:33Z","title":"Exploring and Exploiting Stability in Latent Flow Matching","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-12T01:23:17.812123Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.08398"},"observation_digest":"sha256:0710c33af92bbd7a246d0e5a061a63c997cee796384d0332739abc6a002ad38b","observation_id":"e91e5613-3742-42a8-9ebf-8cd5b9b7dc14","resolution":{"observed_at":"2026-05-12T08:01:30.579202Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.08398","last_updated":"2026-05-29T19:06:27Z","snapshot_observed_at":"2026-08-02T09:24:57.733749Z","submitted_at":"2026-05-08T19:04:33Z","title":"Exploring and Exploiting Stability in Latent Flow Matching","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T22:53:43.702679Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.08398"},"observation_digest":"sha256:fd93068733a8b3ed6882c1e2d860fb6dee9825618df631717837707a04aca4ba","observation_id":"ec22853b-17b5-4668-a8f1-df7b43606a89","resolution":{"observed_at":"2026-07-01T13:35:46.322892Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.10302","last_updated":"2026-05-23T14:04:37Z","snapshot_observed_at":"2026-08-03T12:51:25.405012Z","submitted_at":"2026-05-11T09:57:34Z","title":"Follow the Mean: Reference-Guided Flow Matching","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-12T04:08:34.813884Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.10302"},"observation_digest":"sha256:5c3f34296188e9884f7d21844db0ec2cfad26dcc3f41fc485c1bad2f1162a25b","observation_id":"60f9991e-05b9-444f-b816-b8d4caf68941","resolution":{"observed_at":"2026-05-12T06:36:26.035352Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.10302","last_updated":"2026-05-23T14:04:37Z","snapshot_observed_at":"2026-08-03T12:51:25.405012Z","submitted_at":"2026-05-11T09:57:34Z","title":"Follow the Mean: Reference-Guided Flow Matching","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-13T06:15:03.259674Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.10302"},"observation_digest":"sha256:aa049473011c057fa81a5aa0df58c2d87f59096c80b87a8c791791e37cdb8f64","observation_id":"b8cd3b2f-2740-4449-976e-3e35bf768af2","resolution":{"observed_at":"2026-05-13T06:17:22.945923Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.10302","last_updated":"2026-05-23T14:04:37Z","snapshot_observed_at":"2026-08-03T12:51:25.405012Z","submitted_at":"2026-05-11T09:57:34Z","title":"Follow the Mean: Reference-Guided Flow Matching","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:36.124613Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.10302"},"observation_digest":"sha256:2f14d77395aa7a5abd419dd3489a73961554637f10e196f00d09daffd8da9a18","observation_id":"01f493a1-3313-4567-bb8c-a33d4ebbf802","resolution":{"observed_at":"2026-07-01T14:15:46.855609Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2605.20235","last_updated":"2026-05-16T16:51:10Z","snapshot_observed_at":"2026-07-06T23:30:49.211483Z","submitted_at":"2026-05-16T16:51:10Z","title":"Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-21T07:36:09.475575Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2605.20235"},"observation_digest":"sha256:be3c49dc2d10e5451beb752e5b926597e81fbbe83105c155b0ebbd23d2c6ed27","observation_id":"15d28254-7dc3-4ce6-87d1-c7bc180a1119","resolution":{"observed_at":"2026-05-21T07:39:49.410626Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2606.03820","last_updated":"2026-06-02T16:00:43Z","snapshot_observed_at":"2026-08-09T05:38:05.899888Z","submitted_at":"2026-06-02T16:00:43Z","title":"A Quantitative Approximation Framework for Flow Distillation in Diffusion Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-28T07:58:54.695102Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2606.03820"},"observation_digest":"sha256:b220403a3b5707f9cdbf86fa8128ea9e8e97ab90f7ca67b53d11bcbad5c173ea","observation_id":"bab32fb3-a00c-48a1-a76a-4602e227ed03","resolution":{"observed_at":"2026-07-02T05:56:40.331783Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2606.07271","last_updated":"2026-08-07T10:08:04Z","snapshot_observed_at":"2026-08-10T11:09:41.934140Z","submitted_at":"2026-06-05T13:46:37Z","title":"Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-06-27T22:45:28.530332Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2606.07271"},"observation_digest":"sha256:6a4d56ec0193cae308fcca7db82f9750148c201bfab6e00605c8ffd7d9c044c6","observation_id":"bf3dd4ce-d78b-4d62-a015-d1fade6640b3","resolution":{"observed_at":"2026-07-02T16:27:08.950615Z","resolver_source":"arxiv_id","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":"2410.23594","last_updated":"2024-10-31T03:08:07Z","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?","version":1},"cited_work":{"arxiv_id":"2410.23594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.23594","snapshot_observed_at":"2026-07-02T22:57:26.202515Z","title":"Kaiser et al","venue":null,"work_id":"401bcef7-868c-4d76-918a-d27a71c00240","year":2024},"citing_paper":{"arxiv_id":"2606.08554","last_updated":"2026-06-07T10:14:07Z","snapshot_observed_at":"2026-07-06T23:48:02.118629Z","submitted_at":"2026-06-07T10:14:07Z","title":"A Theoretical Analysis of Memory and Overfitting Phenomena in Stochastic Interpolation Models","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-06-27T18:35:15.196183Z"},"links":{"cited_paper":"/paper/2410.23594","citing_paper":"/paper/2606.08554"},"observation_digest":"sha256:764cb7d36c307f680c6e135075711c824692f6683bb77d6d44fb1c392a163a23","observation_id":"c143f601-3656-44df-be1f-6cab117806da","resolution":{"observed_at":"2026-07-02T22:57:26.203845Z","resolver_source":"arxiv_id","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"}}],"links":{"evidence":"/evidence","html":"/paper/2410.23594/citation-record","integrity":"/paper/2410.23594/integrity","json":"/paper/2410.23594/citation-record.json","paper":"/paper/2410.23594"},"outbound":[],"paper":{"arxiv_id":"2410.23594","last_updated":"2024-10-31T03:08:07Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:42:38.715005Z","submitted_at":"2024-10-31T03:08:07Z","title":"How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2410.23594."}