{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:6LL54QOTFZD7UZXJCRDYSIOMIF","short_pith_number":"pith:6LL54QOT","canonical_record":{"source":{"id":"2410.04642","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-06T22:30:14Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8491fe178cca680313721c656021c913418b317c550706fc72a25cfe51c4739c","abstract_canon_sha256":"dafa59d4b34672a25d0c061139c35936536dff7286ee78a51a19dec62cb9352c"},"schema_version":"1.0"},"canonical_sha256":"f2d7de41d32e47fa66e914478921cc415385199f8b8febef0114ea7f09ce8d37","source":{"kind":"arxiv","id":"2410.04642","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04642","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04642v3","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04642","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"6LL54QOTFZD7","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"6LL54QOTFZD7UZXJ","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"6LL54QOT","created_at":"2026-07-05T10:22:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:6LL54QOTFZD7UZXJCRDYSIOMIF","target":"record","payload":{"canonical_record":{"source":{"id":"2410.04642","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-06T22:30:14Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8491fe178cca680313721c656021c913418b317c550706fc72a25cfe51c4739c","abstract_canon_sha256":"dafa59d4b34672a25d0c061139c35936536dff7286ee78a51a19dec62cb9352c"},"schema_version":"1.0"},"canonical_sha256":"f2d7de41d32e47fa66e914478921cc415385199f8b8febef0114ea7f09ce8d37","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:22:06.368574Z","signature_b64":"LcYtM+q4GWnVJ0qdBQP20N06awwrNVYrn4iQkB41X9czcYMpwySUFYYzGD3EAjdiYGX2U1mjrTMX9nNisoHOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2d7de41d32e47fa66e914478921cc415385199f8b8febef0114ea7f09ce8d37","last_reissued_at":"2026-07-05T10:22:06.368020Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:22:06.368020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.04642","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uE81a4WrJQtplr65itIxscBQnJxU4SWMBxooX8/AIdWAUY+fWFTE3zznijXidUyrLPGT3CJU0Lelzo9g+wCSAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T13:03:09.231953Z"},"content_sha256":"5a719ff97a6329a6021ca28059e5f455c84e23d2a3da3a647cc75d419e1810b5","schema_version":"1.0","event_id":"sha256:5a719ff97a6329a6021ca28059e5f455c84e23d2a3da3a647cc75d419e1810b5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:6LL54QOTFZD7UZXJCRDYSIOMIF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Optimization Landscape of SGD Across the Feature Learning Strength","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexander Atanasov, Alexandru Meterez, Cengiz Pehlevan, James B. Simon","submitted_at":"2024-10-06T22:30:14Z","abstract_excerpt":"We consider neural networks (NNs) where the final layer is down-scaled by a fixed hyperparameter $\\gamma$. Recent work has identified $\\gamma$ as controlling the strength of feature learning. As $\\gamma$ increases, network evolution changes from \"lazy\" kernel dynamics to \"rich\" feature-learning dynamics, with a host of associated benefits including improved performance on common tasks. In this work, we conduct a thorough empirical investigation of the effect of scaling $\\gamma$ across a variety of models and datasets in the online training setting. We first examine the interaction of $\\gamma$ "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04642","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2410.04642/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qp0ylZBJbXUcBzGZ0o6Ui+a2avpez9uZ3Lt3mqbx1Vke+BZuG2jWxo0UiUIeUexcFFJ9M54ztzVRBNMxzyRwBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T13:03:09.232981Z"},"content_sha256":"66079e82b0aa864ba755ba318356961e69c7738bf86427a706c9e5c22eea488d","schema_version":"1.0","event_id":"sha256:66079e82b0aa864ba755ba318356961e69c7738bf86427a706c9e5c22eea488d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/bundle.json","state_url":"https://pith.science/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T13:03:09Z","links":{"resolver":"https://pith.science/pith/6LL54QOTFZD7UZXJCRDYSIOMIF","bundle":"https://pith.science/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/bundle.json","state":"https://pith.science/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6LL54QOTFZD7UZXJCRDYSIOMIF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6LL54QOTFZD7UZXJCRDYSIOMIF","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":"dafa59d4b34672a25d0c061139c35936536dff7286ee78a51a19dec62cb9352c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-06T22:30:14Z","title_canon_sha256":"8491fe178cca680313721c656021c913418b317c550706fc72a25cfe51c4739c"},"schema_version":"1.0","source":{"id":"2410.04642","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04642","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04642v3","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04642","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"6LL54QOTFZD7","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"6LL54QOTFZD7UZXJ","created_at":"2026-07-05T10:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"6LL54QOT","created_at":"2026-07-05T10:22:06Z"}],"graph_snapshots":[{"event_id":"sha256:66079e82b0aa864ba755ba318356961e69c7738bf86427a706c9e5c22eea488d","target":"graph","created_at":"2026-07-05T10:22:06Z","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/2410.04642/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We consider neural networks (NNs) where the final layer is down-scaled by a fixed hyperparameter $\\gamma$. Recent work has identified $\\gamma$ as controlling the strength of feature learning. As $\\gamma$ increases, network evolution changes from \"lazy\" kernel dynamics to \"rich\" feature-learning dynamics, with a host of associated benefits including improved performance on common tasks. In this work, we conduct a thorough empirical investigation of the effect of scaling $\\gamma$ across a variety of models and datasets in the online training setting. We first examine the interaction of $\\gamma$ ","authors_text":"Alexander Atanasov, Alexandru Meterez, Cengiz Pehlevan, James B. Simon","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-06T22:30:14Z","title":"The Optimization Landscape of SGD Across the Feature Learning Strength"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04642","kind":"arxiv","version":3},"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":"sha256:5a719ff97a6329a6021ca28059e5f455c84e23d2a3da3a647cc75d419e1810b5","target":"record","created_at":"2026-07-05T10:22:06Z","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":"dafa59d4b34672a25d0c061139c35936536dff7286ee78a51a19dec62cb9352c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-06T22:30:14Z","title_canon_sha256":"8491fe178cca680313721c656021c913418b317c550706fc72a25cfe51c4739c"},"schema_version":"1.0","source":{"id":"2410.04642","kind":"arxiv","version":3}},"canonical_sha256":"f2d7de41d32e47fa66e914478921cc415385199f8b8febef0114ea7f09ce8d37","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f2d7de41d32e47fa66e914478921cc415385199f8b8febef0114ea7f09ce8d37","first_computed_at":"2026-07-05T10:22:06.368020Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:06.368020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LcYtM+q4GWnVJ0qdBQP20N06awwrNVYrn4iQkB41X9czcYMpwySUFYYzGD3EAjdiYGX2U1mjrTMX9nNisoHOAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:06.368574Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04642","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a719ff97a6329a6021ca28059e5f455c84e23d2a3da3a647cc75d419e1810b5","sha256:66079e82b0aa864ba755ba318356961e69c7738bf86427a706c9e5c22eea488d"],"state_sha256":"650c5f54df19d0e2fc27077ec0f5ea8e1ed3d9f7a2c9593830fb7d9b87a205f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LE1FNHGObILE8H/pay+Wv6Tv9Hfk3kJWgGDkDI7stTSf+nqOeyUFV7zfdBhgoPPu2CmvbglmXTMOYdmR9LVvBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T13:03:09.238910Z","bundle_sha256":"8f8e0ae337063f0a1d66ae1324fe29aceaa461e0bfcd184f8e3a22e187be0a29"}}