{"as_of":"2026-08-09T17:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:702d06f95bc8783bfd2b5875df6b742e66b7a7384cb3da3af927356e0af4e95b","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:09:23.883186Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2507.16697/citation-record","integrity":"/paper/2507.16697/integrity","json":"/paper/2507.16697/citation-record.json","paper":"/paper/2507.16697"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:09:28.436687Z","title":null,"venue":null,"work_id":"8efc8f4d-03a9-4f3c-900e-23d1f285eca1","year":2000},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.250371Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:a95111b9285c3f13fb40145cc3fe5e452d4086e58b40411be733fcea5da5a2db","observation_id":"78ffcee6-d5f5-4b58-90b5-086d3743b0f1","resolution":{"observed_at":"2026-08-06T15:09:28.533438Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:28.217060Z","title":"Paradigms in turbulent combustion research,","venue":null,"work_id":"115792e3-af85-40d3-bbde-2d73eb21a4f4","year":2005},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.371202Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:9519ebb0d1221a1b4cec4b35fc2640805f5bf51e8489d0b6bcae90babfe5030f","observation_id":"c26bd082-1e8d-4638-885e-d6043c977e13","resolution":{"observed_at":"2026-08-06T15:09:28.364742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:28.044242Z","title":"Electromagnetic effects on plasma microturbulence and transport,","venue":null,"work_id":"bcf49b07-37d1-4a13-83db-bc00c950619e","year":2001},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.494665Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:a963d822f0d693d291729dd5c7fbc48cc7963b1ac45de8561b1e1f0a8c562659","observation_id":"e6b7c40a-12f0-4924-97ab-225e59b93d2d","resolution":{"observed_at":"2026-08-06T15:09:28.122789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:27.847309Z","title":"GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the ex- ascale using OpenMP offloading,","venue":null,"work_id":"ff504b81-fca6-4c84-8546-d2d92997d921","year":2025},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.579091Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:9703bcfd53f1cb0e3cc99d4057573d138b16f151f7ab034ca165715dcc71f520","observation_id":"7e0d00e0-57b2-424e-8fd2-26dd4e1c59dc","resolution":{"observed_at":"2026-08-06T15:09:27.954103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10343","last_updated":"2023-12-18T18:16:12Z","snapshot_observed_at":"2026-08-09T14:40:53.774541Z","submitted_at":"2023-01-24T23:19:01Z","title":"ClimaX: A foundation model for weather and climate","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10343","snapshot_observed_at":"2026-08-06T15:09:20.648848Z","title":"Climax: A foundation model for weather and climate,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.648848Z"},"links":{"cited_paper":"/paper/2301.10343","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:e5c688defb383965047396040b4c53f63ca3e569605fb9180834f60c847ebeef","observation_id":"5b36cdb8-09f4-4c94-b336-dd6e1ef737f8","resolution":{"observed_at":"2026-08-06T15:09:20.648848Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.13063","last_updated":"2024-11-21T20:14:58Z","snapshot_observed_at":"2026-08-06T17:51:20.050844Z","submitted_at":"2024-05-20T14:45:18Z","title":"A Foundation Model for the Earth System","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.13063","snapshot_observed_at":"2026-08-06T15:09:20.760766Z","title":"A foundation model for the earth system,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.760766Z"},"links":{"cited_paper":"/paper/2405.13063","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:20322c668bf084ff536c49514cf47aff3da2ac90c3d94688279237512a84685b","observation_id":"14d1893a-c0b8-4cca-a5ef-bd3decc383de","resolution":{"observed_at":"2026-08-06T15:09:20.760766Z","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":"2026-08-06T15:09:27.662819Z","title":"ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability,","venue":null,"work_id":"294e47eb-7e92-4a9e-93f6-881a71206764","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.878021Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:be61cafed24f566ef43cd2b0fd3fc92fc6c3d94c6e12c43a34d7e50a089e1442","observation_id":"895dfbbc-95cc-4e41-887d-50fabd51e2df","resolution":{"observed_at":"2026-08-06T15:09:27.746405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:27.419537Z","title":"A public turbulence database cluster and applications to study lagrangian evolution of velocity increments in turbulence,","venue":null,"work_id":"7c84b6b0-a74f-4e6f-92fc-e46c93f41e97","year":2008},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:20.944601Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:c585cac3b9c6271b05339d80851d06a449433655cfa8ed2e28ad818d90dc53f1","observation_id":"316c0dea-59cf-4c5c-9109-0703d61abf8c","resolution":{"observed_at":"2026-08-06T15:09:27.508890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:27.220789Z","title":"System optimizations for enabling training of extreme long sequence transformer models,","venue":null,"work_id":"dfe46687-2af9-4c7b-bfa4-1b46a0f74553","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.037129Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:74aba14170d6ff7b1ad9423f57a82039d10df0cca7c50f8162880943d3c595e5","observation_id":"60bd9ead-dc3b-48a2-a079-f5b5200b5f38","resolution":{"observed_at":"2026-08-06T15:09:27.314034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:27.052455Z","title":"Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM,","venue":null,"work_id":"65ef6e16-4382-4ed7-8669-d7a512a7b0c3","year":2021},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.148206Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:32046f86996871c81f520c7d7c0f3e3eab926b7a4c2ff89ac895cf2a4be06a30","observation_id":"2529dc1a-cc78-4acf-bd0c-f1f04fafa9f1","resolution":{"observed_at":"2026-08-06T15:09:27.112979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:26.816298Z","title":"RingAttention with Blockwise Transformers for Near-Infinite Context,","venue":null,"work_id":"f4739f5b-cb2d-43fa-99c4-aac89498ab1f","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.222347Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:2f71de0c54426e6f70eaa40d47b060e3c1c80792c21cb5234b31e9c6e6832307","observation_id":"6a0d3513-9a0f-4006-886d-ce8e536cde91","resolution":{"observed_at":"2026-08-06T15:09:26.974443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-06T15:09:21.290561Z","title":"The Llama 3 Herd of Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.290561Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:7cc927c77acdfd6bf3cec855c604d657c44267e7d280730b4f5eb01fb52e42e8","observation_id":"6fc06dd2-4763-47be-823d-be72d40a6be6","resolution":{"observed_at":"2026-08-06T15:09:21.290561Z","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":"2026-08-06T15:09:26.674351Z","title":"Llama3 with 1M Context Length,","venue":null,"work_id":"4d7c56eb-7ccc-451f-ad02-a899be1d3734","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.401249Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:d7eb0681845803407a246540f1f2afb2639c6510ecd3cbc0c97fdef0b78fc5b6","observation_id":"243f0790-ba8f-4ee7-aa7d-1e3d29324cc5","resolution":{"observed_at":"2026-08-06T15:09:26.737637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:26.513027Z","title":"Optimiza- tion of collective communication operations in MPICH,","venue":null,"work_id":"90c1dd9b-6da5-44a4-9257-778ac4dc373c","year":2005},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.504238Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:8891eeb5df71a0e6fc205c59f2c343dddfd8d77732711e86f3f134792a70bcb7","observation_id":"f8c5a209-778e-4ad5-824a-2689f3d135e1","resolution":{"observed_at":"2026-08-06T15:09:26.606603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02994","last_updated":"2024-12-10T16:25:53Z","snapshot_observed_at":"2026-07-06T16:27:47.445841Z","submitted_at":"2023-10-04T17:29:19Z","title":"Multiple Physics Pretraining for Physical Surrogate Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02994","snapshot_observed_at":"2026-08-06T15:09:21.583016Z","title":"Multiple physics pretraining for phys- ical surrogate models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.583016Z"},"links":{"cited_paper":"/paper/2310.02994","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:0be9397d5539f5dd7b3797d5c0a485c2dc56cb69b1548eed71050d8c4b61bcd2","observation_id":"acad507e-5144-41d1-b09f-2d99d78fe08d","resolution":{"observed_at":"2026-08-06T15:09:21.583016Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.20601","last_updated":"2024-12-29T22:13:16Z","snapshot_observed_at":"2026-08-06T09:07:40.224438Z","submitted_at":"2024-12-29T22:13:16Z","title":"MATEY: multiscale adaptive foundation models for spatiotemporal physical systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.20601","snapshot_observed_at":"2026-08-06T15:09:21.687086Z","title":"MATEY: multiscale adaptive founda- tion models for spatiotemporal physical systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.687086Z"},"links":{"cited_paper":"/paper/2412.20601","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:855a1d2a75c461eda0bf5ad6928a5b4b9bfeba38156976fe42a13700184aa68c","observation_id":"b93d2792-2d95-458e-b732-8d0dd6cdcfcf","resolution":{"observed_at":"2026-08-06T15:09:21.687086Z","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":"2026-08-06T15:09:26.330622Z","title":"Super-resolution reconstruction of turbulent flows with machine learning,","venue":null,"work_id":"f10b727f-08ea-42ef-b265-5ec787fd7763","year":2019},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.836373Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:95405780236f861e65012804c125a8bd9262a9057fbcfd92fb9415ed09a9340f","observation_id":"25ee92e8-4cc4-4710-86fc-03fdd1d28318","resolution":{"observed_at":"2026-08-06T15:09:26.394092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.01776","last_updated":"2024-03-14T22:46:25Z","snapshot_observed_at":"2026-07-06T15:37:20.139606Z","submitted_at":"2023-05-29T18:20:28Z","title":"From Zero to Turbulence: Generative Modeling for 3D Flow Simulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.01776","snapshot_observed_at":"2026-08-06T15:09:21.922467Z","title":"From zero to turbulence: Generative modeling for 3D flow simulation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.922467Z"},"links":{"cited_paper":"/paper/2306.01776","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:6ae1e18be2815ea620cbe5828e55d401fd8303a632f0ec18be5fc23210d8ddfa","observation_id":"e17805e2-92c2-41eb-8e04-b0431680e315","resolution":{"observed_at":"2026-08-06T15:09:21.922467Z","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":"2026-08-06T15:09:26.176154Z","title":"A transformer-based convolutional method to model inverse cascade in forced two-dimensional turbulence,","venue":null,"work_id":"161e1036-ae18-446d-9e12-4f51b7fa43ac","year":2025},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:21.977469Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:41eb6f32f3f1fac322acae5f85e1b3eb493b21ae8732e3d0bbf58db880313e96","observation_id":"7c915b87-7db9-43ed-af84-921f7742abcd","resolution":{"observed_at":"2026-08-06T15:09:26.228698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:25.932258Z","title":"Towards physics-informed deep learning for turbulent flow prediction,","venue":null,"work_id":"d2da941a-5e15-42bb-adf4-b783d9017e14","year":2020},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.086892Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:5f7103e407ec6e4ab123810c5351aa84fc237e876ae759bdcf9a43cb91777639","observation_id":"2d2454db-7211-4a60-b92a-feb940aaf3e1","resolution":{"observed_at":"2026-08-06T15:09:26.066848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:25.789555Z","title":"Single-snapshot machine learn- ing for super-resolution of turbulence,","venue":null,"work_id":"4edc7052-5c77-4378-beb2-ff1c42d17f27","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.185227Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:89a6a5b71f7d2ff091fb19f4a31f74e2488af310f07a67c50f0c706f827f268e","observation_id":"be1e7f2d-2891-415d-9a9c-95011279e1ef","resolution":{"observed_at":"2026-08-06T15:09:25.881698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:25.656351Z","title":"A multi-scale hybrid attention swin- transformer-based model for the super-resolution recon- struction of turbulence,","venue":null,"work_id":"1164ec0f-f56e-45fb-b277-f2ceae436233","year":2025},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.266101Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:cefa350b5fc3c12d8ae0a3c520d84f5e8bcf6758c0ad8230a2e372b8acbdb3cc","observation_id":"08cc6e7e-74b3-4f88-8237-e832f5298b4f","resolution":{"observed_at":"2026-08-06T15:09:25.725492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.06050","last_updated":"2024-12-08T20:05:03Z","snapshot_observed_at":"2026-07-06T20:03:33.963070Z","submitted_at":"2024-12-08T20:05:03Z","title":"Concerning the Use of Turbulent Flow Data for Machine Learning","version":1},"cited_work":{"arxiv_id":"2412.06050","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.06050","snapshot_observed_at":"2026-08-06T15:09:23.980088Z","title":"Concerning the Use of Turbulent Flow Data for Machine Learning","venue":"physics.flu-dyn","work_id":"d28396ec-1cd2-4536-ba7a-9a5c2ef617f5","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.423997Z"},"links":{"cited_paper":"/paper/2412.06050","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:0836db8e9dce91cdda86ed51c961d93e3cef667300f681721d4430caed26aa87","observation_id":"c80bef99-268b-407d-a8a4-4cd2b64f159c","resolution":{"observed_at":"2026-08-06T15:09:24.076992Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:25.517115Z","title":"Swin transformer v2: Scaling up capacity and resolution,","venue":null,"work_id":"c02ab004-a697-436e-a530-508cb9eb8b90","year":2022},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.665999Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:4d987ada13ba78f9d9b808eeba6517f1678f22176d8ba89cfeccdf083f06dca0","observation_id":"c163fa82-70ea-4392-b893-9c501b6d991b","resolution":{"observed_at":"2026-08-06T15:09:25.613975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.05799","last_updated":"2018-02-21T04:30:30Z","snapshot_observed_at":"2026-07-06T06:23:45.215820Z","submitted_at":"2018-02-15T23:36:51Z","title":"Horovod: fast and easy distributed deep learning in TensorFlow","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.05799","snapshot_observed_at":"2026-08-06T15:09:22.857853Z","title":"Horovod: fast and easy distributed deep learning in tensorflow,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.857853Z"},"links":{"cited_paper":"/paper/1802.05799","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:a76dd32593c35c2d711aaac19d5ee29a61469e93988bff6ad0272e01a6440bb8","observation_id":"0297f75f-4f1b-4ae3-a4e5-ece3da976231","resolution":{"observed_at":"2026-08-06T15:09:22.857853Z","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":"2026-08-06T15:09:25.298448Z","title":"DISTFLASHATTN: Distributed memory- efficient attention for long-context LLMs training,","venue":null,"work_id":"46dcfd64-17e6-4ffe-8be7-1b17b72a350a","year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:22.961139Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:5f60de9187bb02b02a15a0371a75fbeaaf74257beaa762d357dc4fb842ba778c","observation_id":"ca6dc27b-0560-4256-b160-a9c29bf95463","resolution":{"observed_at":"2026-08-06T15:09:25.396216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.04093","last_updated":"2025-02-09T16:06:53Z","snapshot_observed_at":"2026-08-06T20:00:26.901131Z","submitted_at":"2024-08-07T21:16:55Z","title":"Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.04093","snapshot_observed_at":"2026-08-06T15:09:23.105792Z","title":"Tree Attention: Topology-aware Decod- ing for Long-Context Attention on GPU clusters,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.105792Z"},"links":{"cited_paper":"/paper/2408.04093","citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:2704cc738b0f558573a690717b647d86934bcb43cfd426600ff62e5b289061af","observation_id":"f2b57c26-90b5-4e74-8058-7f15600fd2a8","resolution":{"observed_at":"2026-08-06T15:09:23.105792Z","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":"2026-08-06T15:09:25.145233Z","title":"FlashAt- tention: Fast and memory-efficient exact attention with IO-awareness,","venue":null,"work_id":"033bc641-c978-4176-841f-c196e69d48ff","year":2022},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.208156Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:924d5e563c63996d3e198252d36211029b283cc2bbabe5ab06a261288db34b93","observation_id":"9d8e91ce-dab8-4300-a578-11a78c594117","resolution":{"observed_at":"2026-08-06T15:09:25.208080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:24.975162Z","title":"Johns Hopkins Turbulence Databases (JHTDB),","venue":null,"work_id":"c9f3d2ee-88fe-4b39-944b-63ee67646690","year":2025},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.404399Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:dd2c44f07974c16c3a36145cbce82d10645e11076612b4fcb79dbdac7f6f0ef2","observation_id":"8f6a88d6-00ad-4e06-9214-e95a3f49056e","resolution":{"observed_at":"2026-08-06T15:09:25.060569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:24.800504Z","title":"Dissipation, enstrophy and pressure statistics in turbulence simula- tions at high Reynolds numbers,","venue":null,"work_id":"742f1005-d8cb-46de-ad7b-ed18e0442e21","year":2012},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.622158Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:7f724f531adf28d10f35b6e9ecdcad77673ffa77f4acb100b6419e152507df6e","observation_id":"ff6493ce-705e-4a62-923f-7a78dd56bf7a","resolution":{"observed_at":"2026-08-06T15:09:24.904808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:24.584915Z","title":"Petascale direct numerical simulation of turbulent combustion—fundamental insights towards pre- dictive models,","venue":null,"work_id":"d39a783c-3fa5-4f9e-9de3-9005e564632a","year":2011},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.772191Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:33993d1b44e84e838aaae9d119dbfc1e1bef09be91a31b8b7fdfdd9c4430220c","observation_id":"2edb6c87-aec5-48a7-a3c3-c84613e4d43d","resolution":{"observed_at":"2026-08-06T15:09:24.690960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:24.416615Z","title":"Dynamics of tur- bulence strongly influenced by buoyancy,","venue":null,"work_id":"7e8b3832-8f90-40ad-839c-a8ce4b8d9a68","year":2003},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.840543Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:2344915122a99ec2df38aed907508fd2c00131e148ea6c7c2de9b755f653e599","observation_id":"b39692db-16b4-4d2f-ba3b-bc0d47aa0f8e","resolution":{"observed_at":"2026-08-06T15:09:24.474343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T15:09:24.259945Z","title":"Green500 list – November 2023,","venue":null,"work_id":"e247d67d-0fd5-4d7f-bdba-075cf27e219a","year":2023},"citing_paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T15:09:23.883186Z"},"links":{"citing_paper":"/paper/2507.16697"},"observation_digest":"sha256:56ab52453b1a5c32d4f3f021972286882f5ab66b0e79dfb452036ea4300f3dfa","observation_id":"f21f2208-3ac6-4813-b5fa-406ebf71f09e","resolution":{"observed_at":"2026-08-06T15:09:24.308866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.16697","last_updated":"2025-07-22T15:33:33Z","latest_version":1,"primary_category":"physics.flu-dyn","snapshot_observed_at":"2026-08-07T07:32:50.002138Z","submitted_at":"2025-07-22T15:33:33Z","title":"Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":1,"verified_fuzzy":23},"total_outbound_references":33},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.16697."}