{"as_of":"2026-08-10T14:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec6d1fb0743cd61dee0aa31c6fc8d33276aa889c18fe99d44118b0bd8dfdba16","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T18:57:13.457775Z","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":"2026-06-28T20:52:38.096032Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.06308","last_updated":"2024-10-08T19:35:19Z","snapshot_observed_at":"2026-08-10T08:09:22.405919Z","submitted_at":"2024-10-08T19:35:19Z","title":"Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06308","snapshot_observed_at":"2026-08-09T18:57:13.457775Z","title":"Quantifying training difficulty and accelerating convergence in neural network-based pde solvers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00488","last_updated":"2025-05-29T08:37:00Z","snapshot_observed_at":"2026-08-10T04:18:07.859517Z","submitted_at":"2025-02-01T16:26:53Z","title":"Learn Singularly Perturbed Solutions via Homotopy Dynamics","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-09T18:57:13.457775Z"},"links":{"cited_paper":"/paper/2410.06308","citing_paper":"/paper/2502.00488"},"observation_digest":"sha256:747974c83897844b39c6717890dcc9edf80202f9141c67221bcdc6ae6da5be36","observation_id":"6727ef35-05fd-49ce-8220-d500938e6fb1","resolution":{"observed_at":"2026-08-09T18:57:13.457775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06308","last_updated":"2024-10-08T19:35:19Z","snapshot_observed_at":"2026-08-10T08:09:22.405919Z","submitted_at":"2024-10-08T19:35:19Z","title":"Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06308","snapshot_observed_at":"2026-08-08T21:06:33.447415Z","title":"Quantifying training difficulty and accelerating convergence in neural network-based PDE solvers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04917","last_updated":"2025-06-09T08:48:09Z","snapshot_observed_at":"2026-08-10T03:36:36.356641Z","submitted_at":"2025-02-07T13:36:42Z","title":"Complex Physics-Informed Neural Network","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T21:06:33.447415Z"},"links":{"cited_paper":"/paper/2410.06308","citing_paper":"/paper/2502.04917"},"observation_digest":"sha256:ebba40befc96ccdcd82343fb05b7019d1712f12e13c38892b0d1ab922c696102","observation_id":"01525e0e-14c6-46f9-ae30-78cca8a480d3","resolution":{"observed_at":"2026-08-08T21:06:33.447415Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06308","last_updated":"2024-10-08T19:35:19Z","snapshot_observed_at":"2026-08-10T08:09:22.405919Z","submitted_at":"2024-10-08T19:35:19Z","title":"Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06308","snapshot_observed_at":"2026-08-06T18:50:10.900263Z","title":"arXiv:2410.06308","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07371","last_updated":"2025-07-10T01:50:03Z","snapshot_observed_at":"2026-08-06T18:40:19.137843Z","submitted_at":"2025-07-10T01:50:03Z","title":"Spectral connvergece of random feature method in one dimension","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:50:10.900263Z"},"links":{"cited_paper":"/paper/2410.06308","citing_paper":"/paper/2507.07371"},"observation_digest":"sha256:b86674d57dd6d1e480fe1386ea0098f92b720f84f687a742337324b0898d0bb1","observation_id":"ea313a96-e5d7-4241-baa1-3aa92462eac6","resolution":{"observed_at":"2026-08-06T18:50:10.900263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06308","last_updated":"2024-10-08T19:35:19Z","snapshot_observed_at":"2026-08-10T08:09:22.405919Z","submitted_at":"2024-10-08T19:35:19Z","title":"Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers","version":1},"cited_work":{"arxiv_id":"2410.06308","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.06308","snapshot_observed_at":"2026-06-28T20:52:38.096032Z","title":"arXiv preprint arXiv:2410.06308 , year=","venue":null,"work_id":"8c01e5d3-52c1-4349-8186-188cd1d2ea91","year":null},"citing_paper":{"arxiv_id":"2606.00643","last_updated":"2026-05-30T09:38:48Z","snapshot_observed_at":"2026-08-08T06:28:22.916530Z","submitted_at":"2026-05-30T09:38:48Z","title":"Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-06-28T18:18:04.127372Z"},"links":{"cited_paper":"/paper/2410.06308","citing_paper":"/paper/2606.00643"},"observation_digest":"sha256:8eea9144f18c1662a0af9a85670f1371acb50662a2479bc4c7a62e0046c38037","observation_id":"04cc1c4d-b456-445a-a3d5-1227484d32f9","resolution":{"observed_at":"2026-06-28T20:52:38.098168Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.06308/citation-record","integrity":"/paper/2410.06308/integrity","json":"/paper/2410.06308/citation-record.json","paper":"/paper/2410.06308"},"outbound":[],"paper":{"arxiv_id":"2410.06308","last_updated":"2024-10-08T19:35:19Z","latest_version":1,"primary_category":"math.NA","snapshot_observed_at":"2026-08-10T08:09:22.405919Z","submitted_at":"2024-10-08T19:35:19Z","title":"Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers"},"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 4 inbound Pith citation observations for arXiv:2410.06308."}