{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:R5ESN5GXWVB6NPF3OZYKN4ECVK","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":"c7ec76e787038b1428f8c1af4d8cac1988afd3efba9d56b1cab460d2576c5f7b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-14T04:21:25Z","title_canon_sha256":"88bd47a330c550e034500cef78a708faba5d99b5d55324c2d5c81dc07c56b30c"},"schema_version":"1.0","source":{"id":"2301.05816","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.05816","created_at":"2026-07-05T06:06:57Z"},{"alias_kind":"arxiv_version","alias_value":"2301.05816v4","created_at":"2026-07-05T06:06:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.05816","created_at":"2026-07-05T06:06:57Z"},{"alias_kind":"pith_short_12","alias_value":"R5ESN5GXWVB6","created_at":"2026-07-05T06:06:57Z"},{"alias_kind":"pith_short_16","alias_value":"R5ESN5GXWVB6NPF3","created_at":"2026-07-05T06:06:57Z"},{"alias_kind":"pith_short_8","alias_value":"R5ESN5GX","created_at":"2026-07-05T06:06:57Z"}],"graph_snapshots":[{"event_id":"sha256:79d587852b1473087b88d93df0b2dd1ad20a3e88bd9cf1d13e363c1234f84235","target":"graph","created_at":"2026-07-05T06:06:57Z","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/2301.05816/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spectral bias is an important observation of neural network training, stating that the network will learn a low frequency representation of the target function before converging to higher frequency components. This property is interesting due to its link to good generalization in over-parameterized networks. However, in low dimensional settings, a severe spectral bias occurs that obstructs convergence to high frequency components entirely. In order to overcome this limitation, one can encode the inputs using a high frequency sinusoidal encoding. Previous works attempted to explain this phenome","authors_text":"John Lazzari, Xiuwen Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-14T04:21:25Z","title":"Understanding the Spectral Bias of Coordinate Based MLPs Via Training Dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.05816","kind":"arxiv","version":4},"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":"sha256:07745141f816bc5fa9d71f9605f67c5573698806b7c6ec34c8b3188b242944dc","target":"record","created_at":"2026-07-05T06:06:57Z","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":"c7ec76e787038b1428f8c1af4d8cac1988afd3efba9d56b1cab460d2576c5f7b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-14T04:21:25Z","title_canon_sha256":"88bd47a330c550e034500cef78a708faba5d99b5d55324c2d5c81dc07c56b30c"},"schema_version":"1.0","source":{"id":"2301.05816","kind":"arxiv","version":4}},"canonical_sha256":"8f4926f4d7b543e6bcbb7670a6f082aab4a1c1a0dbcb983d8b43b0d637c97fcc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f4926f4d7b543e6bcbb7670a6f082aab4a1c1a0dbcb983d8b43b0d637c97fcc","first_computed_at":"2026-07-05T06:06:57.223064Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:06:57.223064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dwI+rOabqro2C1copQCnADp0GZ9svAUAjD5EaiLmPDk5duvmz5HQtSgx1vMFG4vPgjV2Drjyomz2gjEqpP+iDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:06:57.223482Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.05816","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:07745141f816bc5fa9d71f9605f67c5573698806b7c6ec34c8b3188b242944dc","sha256:79d587852b1473087b88d93df0b2dd1ad20a3e88bd9cf1d13e363c1234f84235"],"state_sha256":"f35b0f1b752b5f1a8930376c29a1c6f70d9cd87ce42e813b2561bbe8c59bc3b3"}