{"as_of":"2026-08-18T10:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a94c506a9554b41f189af651d21c989a04d0ed9610f16b3cb04f4360345eeea9","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":"2026-08-18T06:34:40.430872+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":"2026-08-06T12:39:09.308337Z","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":"2026-07-04T12:59:52.081520Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.02681","last_updated":"2022-12-28T16:52:12Z","snapshot_observed_at":"2026-08-17T16:53:26.885610Z","submitted_at":"2022-09-06T17:51:52Z","title":"How important are activation functions in regression and classification? A survey, performance comparison, and future directions","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.02681","snapshot_observed_at":"2026-08-06T12:39:09.308337Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.22090","last_updated":"2025-07-29T09:21:57Z","snapshot_observed_at":"2026-08-15T09:17:32.697246Z","submitted_at":"2025-07-29T09:21:57Z","title":"Hybrid activation functions for deep neural networks: S3 and S4 -- a novel approach to gradient flow optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T12:39:09.308337Z"},"links":{"cited_paper":"/paper/2209.02681","citing_paper":"/paper/2507.22090"},"observation_digest":"sha256:61fa9bd6f97baf9b5ec643283c576143289e2251e8494fb7271e637306b9de4f","observation_id":"bb50c474-12e0-49d8-a0b5-880a7269d3d6","resolution":{"observed_at":"2026-08-06T12:39:09.308337Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.02681","last_updated":"2022-12-28T16:52:12Z","snapshot_observed_at":"2026-08-17T16:53:26.885610Z","submitted_at":"2022-09-06T17:51:52Z","title":"How important are activation functions in regression and classification? A survey, performance comparison, and future directions","version":6},"cited_work":{"arxiv_id":"2209.02681","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.02681","snapshot_observed_at":"2026-07-04T12:59:52.081520Z","title":"Jagtap and George Em Karniadakis.How important are activation functions in regression and classification? A survey, performance comparison, and future directions","venue":null,"work_id":"3c0b4f1c-1904-4e73-8e17-5de1643e9ed5","year":2022},"citing_paper":{"arxiv_id":"2606.23874","last_updated":"2026-06-22T19:17:25Z","snapshot_observed_at":"2026-08-14T08:08:58.893770Z","submitted_at":"2026-06-22T19:17:25Z","title":"Identifying structural design principles shaping the computational abilities of recurrent neural networks","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-26T05:43:22.840503Z"},"links":{"cited_paper":"/paper/2209.02681","citing_paper":"/paper/2606.23874"},"observation_digest":"sha256:6b2c077c25ef538fbf9391849e1382e03195311445a3deebd9d01f4e6188371d","observation_id":"6630d072-c94b-4099-8c24-514ad28773d4","resolution":{"observed_at":"2026-07-04T12:59:52.082992Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2209.02681/citation-record","integrity":"/paper/2209.02681/integrity","json":"/paper/2209.02681/citation-record.json","paper":"/paper/2209.02681"},"outbound":[],"paper":{"arxiv_id":"2209.02681","last_updated":"2022-12-28T16:52:12Z","latest_version":6,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T16:53:26.885610Z","submitted_at":"2022-09-06T17:51:52Z","title":"How important are activation functions in regression and classification? A survey, performance comparison, and future directions"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.02681."}