{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WLCBSH7AA7KU6MONNKEC54K2RQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f8a36aa1890568139ee6684d8855aaec605c6e36aaab47b04f1b3db50d5551e6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T18:59:09Z","title_canon_sha256":"5d44781769b834ab9aac79df816be29c3957d8d1f056564fe18be3b5c717304a"},"schema_version":"1.0","source":{"id":"2211.12494","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.12494","created_at":"2026-07-05T05:18:17Z"},{"alias_kind":"arxiv_version","alias_value":"2211.12494v1","created_at":"2026-07-05T05:18:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.12494","created_at":"2026-07-05T05:18:17Z"},{"alias_kind":"pith_short_12","alias_value":"WLCBSH7AA7KU","created_at":"2026-07-05T05:18:17Z"},{"alias_kind":"pith_short_16","alias_value":"WLCBSH7AA7KU6MON","created_at":"2026-07-05T05:18:17Z"},{"alias_kind":"pith_short_8","alias_value":"WLCBSH7A","created_at":"2026-07-05T05:18:17Z"}],"graph_snapshots":[{"event_id":"sha256:3995a22a21054eb223bdfc775ff737c3cd584d47a9bd57df036b7ed4a81fff8d","target":"graph","created_at":"2026-07-05T05:18:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2211.12494/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generalized Zero-Shot Learning (GZSL) aims to train a classifier that can generalize to unseen classes, using a set of attributes as auxiliary information, and the visual features extracted from a pre-trained convolutional neural network. While recent GZSL methods have explored various techniques to leverage the capacity of these features, there has been an extensive growth of representation learning techniques that remain under-explored. In this work, we investigate the utility of different GZSL methods when using different feature extractors, and examine how these models' pre-training object","authors_text":"James Seale Smith, Leonid Karlinsky, Paola Cascante-Bonilla, Vicente Ordonez, Yanjun Qi","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T18:59:09Z","title":"On the Transferability of Visual Features in Generalized Zero-Shot Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.12494","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:681fa9bc3929ee3f111d5e9d5d01696d5a69d450df7944812315c91d01f4a5ff","target":"record","created_at":"2026-07-05T05:18:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f8a36aa1890568139ee6684d8855aaec605c6e36aaab47b04f1b3db50d5551e6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T18:59:09Z","title_canon_sha256":"5d44781769b834ab9aac79df816be29c3957d8d1f056564fe18be3b5c717304a"},"schema_version":"1.0","source":{"id":"2211.12494","kind":"arxiv","version":1}},"canonical_sha256":"b2c4191fe007d54f31cd6a882ef15a8c311dcc535c5a401be63790b06ec05d03","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b2c4191fe007d54f31cd6a882ef15a8c311dcc535c5a401be63790b06ec05d03","first_computed_at":"2026-07-05T05:18:17.663950Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:18:17.663950Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N98VMO3mTW2T9Ml2/Zb6OTXni+YOzuakd8UsHE89xoCGHoY78Gc56LBVS3qr+73A39SHkFFgsQqkY2lWPfDMCA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:18:17.664355Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.12494","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:681fa9bc3929ee3f111d5e9d5d01696d5a69d450df7944812315c91d01f4a5ff","sha256:3995a22a21054eb223bdfc775ff737c3cd584d47a9bd57df036b7ed4a81fff8d"],"state_sha256":"b89a2f3ec0bf957261ce8dde343209eb6682aade498b95b152d0203459454703"}