{"as_of":"2026-08-22T14:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5cfd49e3742fa5468c02e0569b66d6667df0ce74b7763d76e98a4f89e058d005","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T02:04:24.179820Z","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":"2026-07-03T19:08:50.294428Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.18484","last_updated":"2024-02-14T13:22:08Z","snapshot_observed_at":"2026-08-22T00:06:14.872323Z","submitted_at":"2023-05-29T12:06:53Z","title":"Neural Fourier Transform: A General Approach to Equivariant Representation Learning","version":2},"cited_work":{"arxiv_id":"2305.18484","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.18484","snapshot_observed_at":"2026-07-03T19:08:50.294428Z","title":"Neural fourier transform: A general approach to equivariant representation learning.arXiv preprint arXiv:2305.18484","venue":null,"work_id":"680ede74-327a-4d6a-9515-d5ac4c46cba5","year":2023},"citing_paper":{"arxiv_id":"2605.15725","last_updated":"2026-05-15T08:22:37Z","snapshot_observed_at":"2026-08-06T08:15:14.018564Z","submitted_at":"2026-05-15T08:22:37Z","title":"DiLA: Disentangled Latent Action World Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-20T19:35:37.527479Z"},"links":{"cited_paper":"/paper/2305.18484","citing_paper":"/paper/2605.15725"},"observation_digest":"sha256:0786e2bfd10ebb5c772b730157296b9a7dbc0d8c38addedde72456947d11a21c","observation_id":"e532c56d-2058-4223-9c1a-236b0c3ebb6d","resolution":{"observed_at":"2026-05-20T19:38:56.351181Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.18484","last_updated":"2024-02-14T13:22:08Z","snapshot_observed_at":"2026-08-22T00:06:14.872323Z","submitted_at":"2023-05-29T12:06:53Z","title":"Neural Fourier Transform: A General Approach to Equivariant Representation Learning","version":2},"cited_work":{"arxiv_id":"2305.18484","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.18484","snapshot_observed_at":"2026-07-03T19:08:50.294428Z","title":"Neural fourier transform: A general approach to equivariant representation learning.arXiv preprint arXiv:2305.18484","venue":null,"work_id":"680ede74-327a-4d6a-9515-d5ac4c46cba5","year":2023},"citing_paper":{"arxiv_id":"2606.17782","last_updated":"2026-06-16T10:58:51Z","snapshot_observed_at":"2026-08-19T17:06:11.375149Z","submitted_at":"2026-06-16T10:58:51Z","title":"Blind Recovery of Latent Domains via Unsupervised Symmetry Discovery","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T02:04:24.179820Z"},"links":{"cited_paper":"/paper/2305.18484","citing_paper":"/paper/2606.17782"},"observation_digest":"sha256:b40eb0fd813b6f539c825388fb03b8c15ea0c0c4b0a93fff07cebc50c5c037e1","observation_id":"82924422-179b-43ca-a3e7-f081f6b42367","resolution":{"observed_at":"2026-07-03T19:08:50.296207Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.18484/citation-record","integrity":"/paper/2305.18484/integrity","json":"/paper/2305.18484/citation-record.json","paper":"/paper/2305.18484"},"outbound":[],"paper":{"arxiv_id":"2305.18484","last_updated":"2024-02-14T13:22:08Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-22T00:06:14.872323Z","submitted_at":"2023-05-29T12:06:53Z","title":"Neural Fourier Transform: A General Approach to Equivariant Representation Learning"},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.18484."}