{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2FZLUUASHLL3EMKY3TKCOJD7ZF","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":"6b74fe0ee3e0992936723633f372115d36d4283a12137da948553dafe3a6fd2a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-10T20:41:40Z","title_canon_sha256":"186dbd1ce3545051270800b97da5d6908cf81dad8b562aca2f8e124e028fb11b"},"schema_version":"1.0","source":{"id":"2304.04858","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04858","created_at":"2026-07-05T05:59:52Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04858v1","created_at":"2026-07-05T05:59:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04858","created_at":"2026-07-05T05:59:52Z"},{"alias_kind":"pith_short_12","alias_value":"2FZLUUASHLL3","created_at":"2026-07-05T05:59:52Z"},{"alias_kind":"pith_short_16","alias_value":"2FZLUUASHLL3EMKY","created_at":"2026-07-05T05:59:52Z"},{"alias_kind":"pith_short_8","alias_value":"2FZLUUAS","created_at":"2026-07-05T05:59:52Z"}],"graph_snapshots":[{"event_id":"sha256:6ea34faa389ef4bdb8aacb2cc3608edadf2261fc440bbad54b551e7c67b190f7","target":"graph","created_at":"2026-07-05T05:59:52Z","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/2304.04858/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, a number of iterative learning methods have been introduced to improve generalization. These typically rely on training for longer periods of time in exchange for improved generalization. LLF (later-layer-forgetting) is a state-of-the-art method in this category. It strengthens learning in early layers by periodically re-initializing the last few layers of the network. Our principal innovation in this work is to use Simulated annealing in EArly Layers (SEAL) of the network in place of re-initialization of later layers. Essentially, later layers go through the normal gradient descent ","authors_text":"AmirMohammad Sarfi, Eugene Belilovsky, Mirco Ravanelli, Muawiz Chaudhary, Nasir M. Khalid, Sudhir Mudur, Zahra Karimpour","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-10T20:41:40Z","title":"Simulated Annealing in Early Layers Leads to Better Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04858","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:aa9dcdc82c87f647dfed8006a1aa9cee674d45f6db930d82fd939f9fad31b78e","target":"record","created_at":"2026-07-05T05:59:52Z","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":"6b74fe0ee3e0992936723633f372115d36d4283a12137da948553dafe3a6fd2a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-10T20:41:40Z","title_canon_sha256":"186dbd1ce3545051270800b97da5d6908cf81dad8b562aca2f8e124e028fb11b"},"schema_version":"1.0","source":{"id":"2304.04858","kind":"arxiv","version":1}},"canonical_sha256":"d172ba50123ad7b23158dcd427247fc95e7e61ed6e3cac0eae19b54ad46a7116","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d172ba50123ad7b23158dcd427247fc95e7e61ed6e3cac0eae19b54ad46a7116","first_computed_at":"2026-07-05T05:59:52.523081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:52.523081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qfgk7JG3Nft/t5Jgur3hCavixVsdGupmFbLxiXmHMm7zXkZR1ICn+O7ZKCnRx1ES5ONoPI+BoAW9FBPOy306Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:52.523493Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.04858","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa9dcdc82c87f647dfed8006a1aa9cee674d45f6db930d82fd939f9fad31b78e","sha256:6ea34faa389ef4bdb8aacb2cc3608edadf2261fc440bbad54b551e7c67b190f7"],"state_sha256":"c9bd63dd748f8e00ee9cb8b23212dcc62598816424690b47fd3819875106e0cb"}