{"as_of":"2026-08-11T15:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:217310038407c8e736336413d68f7373a101b10680a5cba41a2352216ae4b2ef","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T19:32:41.842355Z","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":"2026-07-02T02:06:27.737834Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2412.08079","last_updated":"2026-04-07T04:07:30Z","snapshot_observed_at":"2026-07-06T20:05:01.312121Z","submitted_at":"2024-12-11T03:52:17Z","title":"Regional climate risk assessment from climate models using probabilistic machine learning","version":3},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-23T07:26:44.351983Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2412.08079"},"observation_digest":"sha256:587bd8fe602b4b40c9d3c36930ef9c3af5611a157ec1059cd6eabc05ace50233","observation_id":"fd9447e1-4904-450c-baa8-5928daddffee","resolution":{"observed_at":"2026-05-23T07:27:42.627465Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-08-10T19:32:41.842355Z","title":"Molinaro, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.09987","last_updated":"2025-01-17T06:56:51Z","snapshot_observed_at":"2026-08-10T21:50:24.814165Z","submitted_at":"2025-01-17T06:56:51Z","title":"On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs","version":1},"reference_index":130,"source":"pdf_text","source_observed_at":"2026-08-10T19:32:41.842355Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2501.09987"},"observation_digest":"sha256:0eb1616f5d61dbaad6c98b6bd8a84738fc4ceb6a7074209db6c9c137c74e4148","observation_id":"a6b48db0-e5ac-4833-8f3f-b6c513bc98a1","resolution":{"observed_at":"2026-08-10T19:32:41.842355Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2502.01476","last_updated":"2026-05-21T15:15:31Z","snapshot_observed_at":"2026-08-02T22:09:10.725557Z","submitted_at":"2025-02-03T16:06:56Z","title":"Neuro-Symbolic AI for Analytical Solutions of Differential Equations","version":4},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-23T03:33:09.370984Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2502.01476"},"observation_digest":"sha256:530bd2a2e6794d68cbba15c9fe7e37d747956af99fe962086fb27f7a774fd6b8","observation_id":"007485de-2e30-4063-9ac1-83877de09611","resolution":{"observed_at":"2026-05-23T03:35:21.208948Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-08-07T10:54:50.371643Z","title":"Generative ai for fast and accurate statistical computation of fluids","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03979","last_updated":"2025-06-05T04:27:46Z","snapshot_observed_at":"2026-08-08T12:18:48.758557Z","submitted_at":"2025-06-04T14:09:25Z","title":"Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach","version":2},"reference_index":204,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:50.371643Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2506.03979"},"observation_digest":"sha256:107b06f7da28d1dfeb41137429897e615d7db284c6c999838d435083374e822b","observation_id":"a9c304a8-30c0-4887-8187-a991a1757c22","resolution":{"observed_at":"2026-08-07T10:54:50.371643Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-08-06T10:46:04.944814Z","title":"Molinaro , author S","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.23662","last_updated":"2025-07-31T15:40:14Z","snapshot_observed_at":"2026-08-10T15:53:08.311017Z","submitted_at":"2025-07-31T15:40:14Z","title":"Modeling turbulent and self-gravitating fluids with Fourier neural operators","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T10:46:04.944814Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2507.23662"},"observation_digest":"sha256:0d81702250512a055e03a9628e5a85b79905ee329a8adfc802383b5625f3c3ba","observation_id":"bb874153-65b5-49ab-b2f3-d5097d445493","resolution":{"observed_at":"2026-08-06T10:46:04.944814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2603.21210","last_updated":"2026-06-30T12:08:53Z","snapshot_observed_at":"2026-08-11T09:00:56.598081Z","submitted_at":"2026-03-22T13:08:01Z","title":"Pretrained Video Models as Differentiable Physics Simulators for Urban Wind Flows","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-15T07:01:08.953346Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2603.21210"},"observation_digest":"sha256:b6bbbac22a384f0b136752ea0461c239a78fc75cac88a152c127d7972977c492","observation_id":"a6cabe03-f816-4e6b-a9ca-9798a8745fae","resolution":{"observed_at":"2026-05-15T07:05:11.568116Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2604.08586","last_updated":"2026-03-30T10:08:20Z","snapshot_observed_at":"2026-08-11T03:05:54.115336Z","submitted_at":"2026-03-30T10:08:20Z","title":"FluidFlow: a flow-matching generative model for fluid dynamics surrogates on unstructured meshes","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-14T21:20:56.281902Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2604.08586"},"observation_digest":"sha256:2d143acb41d5ef04bc88de1a8f22072a68c831189ec76c60270c19d28506fded","observation_id":"45028dbb-24d3-40fc-91cc-2f862a1ff9cd","resolution":{"observed_at":"2026-05-14T21:22:59.265783Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-08-02T14:48:36.222253Z","title":"Generative ai for fast and accurate statistical computation of fluids.arXiv preprint arXiv:2409.18359, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2605.05540","last_updated":"2026-07-27T15:13:41Z","snapshot_observed_at":"2026-08-02T14:48:29.228330Z","submitted_at":"2026-05-07T00:41:47Z","title":"Autoregressive One-Step Generative Modeling for Dynamical System Forecasting","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-02T14:48:36.222253Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2605.05540"},"observation_digest":"sha256:55743c181e4ddb55f645820dc251d744d773590b394810ba20fd9f05f2ae9ebe","observation_id":"dd3322ac-ac10-4e18-bacc-dd8a909626c5","resolution":{"observed_at":"2026-08-02T14:48:36.222253Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2605.07959","last_updated":"2026-05-08T16:22:08Z","snapshot_observed_at":"2026-07-06T23:20:15.696237Z","submitted_at":"2026-05-08T16:22:08Z","title":"Convergent Stochastic Training of Attention and Understanding LoRA","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-05-11T02:48:35.907351Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2605.07959"},"observation_digest":"sha256:26a4929eade21c5967e649491210bb7b5bbe8d41db5228bf689ed543380c9b20","observation_id":"44e2a361-14ee-4293-83d1-87af4bd9c7d7","resolution":{"observed_at":"2026-05-11T03:05:55.065038Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids","version":2},"cited_work":{"arxiv_id":"2409.18359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18359","snapshot_observed_at":"2026-07-02T02:06:27.737834Z","title":"Generative AI for fast and accurate statistical computation of fluids","venue":null,"work_id":"63a9e0d3-0d27-4364-bdff-c22529067fbb","year":2024},"citing_paper":{"arxiv_id":"2606.03936","last_updated":"2026-06-02T17:26:15Z","snapshot_observed_at":"2026-08-08T03:17:34.020268Z","submitted_at":"2026-06-02T17:26:15Z","title":"Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-28T11:10:52.822919Z"},"links":{"cited_paper":"/paper/2409.18359","citing_paper":"/paper/2606.03936"},"observation_digest":"sha256:292666ae50dc87fbb46c5eeb0ce150c15ebf1438457836b89048904eff125f04","observation_id":"8236de4c-fcbf-4f26-ba37-885a1775b3cf","resolution":{"observed_at":"2026-07-02T02:06:27.740030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.18359/citation-record","integrity":"/paper/2409.18359/integrity","json":"/paper/2409.18359/citation-record.json","paper":"/paper/2409.18359"},"outbound":[],"paper":{"arxiv_id":"2409.18359","last_updated":"2025-02-03T02:58:10Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T10:06:40.901234Z","submitted_at":"2024-09-27T00:26:18Z","title":"Generative AI for fast and accurate statistical computation of fluids"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2409.18359."}