{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:DFPIDT2JYFKNK34NVDZO7GMGK4","short_pith_number":"pith:DFPIDT2J","schema_version":"1.0","canonical_sha256":"195e81cf49c154d56f8da8f2ef9986573bf4527f511f0fad5d472b1f73d7448d","source":{"kind":"arxiv","id":"1907.07844","version":1},"attestation_state":"computed","paper":{"title":"Growing a Brain: Fine-Tuning by Increasing Model Capacity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Deva Ramanan, Martial Hebert, Yu-Xiong Wang","submitted_at":"2019-07-18T02:20:18Z","abstract_excerpt":"CNNs have made an undeniable impact on computer vision through the ability to learn high-capacity models with large annotated training sets. One of their remarkable properties is the ability to transfer knowledge from a large source dataset to a (typically smaller) target dataset. This is usually accomplished through fine-tuning a fixed-size network on new target data. Indeed, virtually every contemporary visual recognition system makes use of fine-tuning to transfer knowledge from ImageNet. In this work, we analyze what components and parameters change during fine-tuning, and discover that in"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1907.07844","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-18T02:20:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4fae4c66ec5f69154f7c599cca9dd74f55259dcbdef8ca2a2f7ebda1b7313346","abstract_canon_sha256":"23940eec2f113a7daf34fc1172c26455f201d021bf20102416cbbe003fb4320d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:16.014621Z","signature_b64":"NDsln3MbuxNFVBk0QEoHYRE2yMJWMtawnH/SfChPfGmMf9Q7XR/ZtXE4nL9p+AQ+n1pEcR8dgejE2GIFiBvbCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"195e81cf49c154d56f8da8f2ef9986573bf4527f511f0fad5d472b1f73d7448d","last_reissued_at":"2026-05-17T23:40:16.013815Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:16.013815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Growing a Brain: Fine-Tuning by Increasing Model Capacity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Deva Ramanan, Martial Hebert, Yu-Xiong Wang","submitted_at":"2019-07-18T02:20:18Z","abstract_excerpt":"CNNs have made an undeniable impact on computer vision through the ability to learn high-capacity models with large annotated training sets. One of their remarkable properties is the ability to transfer knowledge from a large source dataset to a (typically smaller) target dataset. This is usually accomplished through fine-tuning a fixed-size network on new target data. Indeed, virtually every contemporary visual recognition system makes use of fine-tuning to transfer knowledge from ImageNet. In this work, we analyze what components and parameters change during fine-tuning, and discover that in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07844","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1907.07844","created_at":"2026-05-17T23:40:16.013915+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.07844v1","created_at":"2026-05-17T23:40:16.013915+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07844","created_at":"2026-05-17T23:40:16.013915+00:00"},{"alias_kind":"pith_short_12","alias_value":"DFPIDT2JYFKN","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"DFPIDT2JYFKNK34N","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"DFPIDT2J","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4","json":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4.json","graph_json":"https://pith.science/api/pith-number/DFPIDT2JYFKNK34NVDZO7GMGK4/graph.json","events_json":"https://pith.science/api/pith-number/DFPIDT2JYFKNK34NVDZO7GMGK4/events.json","paper":"https://pith.science/paper/DFPIDT2J"},"agent_actions":{"view_html":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4","download_json":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4.json","view_paper":"https://pith.science/paper/DFPIDT2J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.07844&json=true","fetch_graph":"https://pith.science/api/pith-number/DFPIDT2JYFKNK34NVDZO7GMGK4/graph.json","fetch_events":"https://pith.science/api/pith-number/DFPIDT2JYFKNK34NVDZO7GMGK4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4/action/storage_attestation","attest_author":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4/action/author_attestation","sign_citation":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4/action/citation_signature","submit_replication":"https://pith.science/pith/DFPIDT2JYFKNK34NVDZO7GMGK4/action/replication_record"}},"created_at":"2026-05-17T23:40:16.013915+00:00","updated_at":"2026-05-17T23:40:16.013915+00:00"}