{"as_of":"2026-08-19T16:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8794234c3e22a703bef5d49265633f43eebd2f3b658f2b575e46c3f4e5f4edbe","coverage":[{"denominator":7,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T04:58:17.476379Z","state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2412.00884/citation-record","integrity":"/paper/2412.00884/integrity","json":"/paper/2412.00884/citation-record.json","paper":"/paper/2412.00884"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:58:17.575189Z","title":"Understanding intermediate layers using linear classifier probes","venue":null,"work_id":"bb4642fc-bdaf-4f48-90e9-6fde22ac8c50","year":2017},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.448731Z"},"links":{"citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:53b41e374561b85b874aa5926d474db96d8136ee9d73e83fd63e66971f5b0143","observation_id":"637b4c0c-0914-4bf3-a7ac-d7751793f8d6","resolution":{"observed_at":"2026-08-12T04:58:17.579708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-12T04:58:17.562297Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","venue":null,"work_id":"08ae8947-45c2-4479-9b49-b08c26ea6ad9","year":2021},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.453585Z"},"links":{"citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:829f1a1a1035a954936f3147cd0e360ea6ee8aa2a9259991c4f78b7c311f7aa5","observation_id":"d3d099fb-35d7-462c-8b13-a0a606904a56","resolution":{"observed_at":"2026-08-12T04:58:17.566574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09028","last_updated":"2022-09-28T00:10:02Z","snapshot_observed_at":"2026-08-16T17:20:24.255004Z","submitted_at":"2022-02-18T05:21:28Z","title":"On the Implicit Bias Towards Minimal Depth of Deep Neural Networks","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.09028","snapshot_observed_at":"2026-08-12T04:58:17.457623Z","title":"2022.doi: 10.48550/ARXIV.2202.09028","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.457623Z"},"links":{"cited_paper":"/paper/2202.09028","citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:40303eabbea3515a574cb38dbdc40f1d8eedf6589210e4d53571cbd4ee425b83","observation_id":"9a6f1124-cdda-4db5-b28d-a4d2e0082588","resolution":{"observed_at":"2026-08-12T04:58:17.457623Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T04:58:17.462144Z","title":"Prevalenceofneuralcollapseduring the terminal phase of deep learning training","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.462144Z"},"links":{"citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:24d8cc7833f23240ae1d67d1ee5c908de344b613dcdf03d34ceac19c1ae104b4","observation_id":"3df788c0-81dc-4ea0-94ae-8218d5607b4d","resolution":{"observed_at":"2026-08-12T04:58:17.462144Z","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":"2026-08-12T04:58:17.549629Z","title":"Attention is all you need","venue":null,"work_id":"29125c6b-a8bd-46fe-8022-e67ef9c379a5","year":2017},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.466672Z"},"links":{"citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:a858293ed13f7d5915b413302bb90bc139d6db73350dbf23cd2b7edb7fb8a59a","observation_id":"07be996f-545d-4f9c-830e-769484f8c2ec","resolution":{"observed_at":"2026-08-12T04:58:17.553483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-08-13T15:13:33.081929Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-12T04:58:17.471009Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.471009Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:d55bc844ea9ce3ff61ca18dd0f551b3d4ae193d72421df4da7d3986672c27fb3","observation_id":"f9466ab6-b8fa-4b7c-9a23-e56b2bf810fc","resolution":{"observed_at":"2026-08-12T04:58:17.471009Z","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":"2026-08-12T04:58:17.535406Z","title":"A Geometric Analysis of Neural Collapse with Unconstrained Features","venue":null,"work_id":"87a3e6a6-3692-4495-80f7-cc3dade582d0","year":2021},"citing_paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:17.476379Z"},"links":{"citing_paper":"/paper/2412.00884"},"observation_digest":"sha256:0208318c182d1a5091d383df8e6a66dd0600c7de27a9ff433ec6d6abbc7c21d5","observation_id":"bd7253a3-5948-4127-8b2c-51f0dc842dd9","resolution":{"observed_at":"2026-08-12T04:58:17.541208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.00884","last_updated":"2024-12-01T16:44:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-19T13:30:08.442989Z","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks"},"reference_resolution":{"displayed":7,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":4},"total_outbound_references":7},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2412.00884."}