{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:G2CJPE54L2SF2PX7YOQXWSSIWU","short_pith_number":"pith:G2CJPE54","canonical_record":{"source":{"id":"2305.18411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-28T17:09:32Z","cross_cats_sorted":[],"title_canon_sha256":"4c71c3c77365bb51c6481a163de7680e83a484e8f36fcda60ed285d1be092b49","abstract_canon_sha256":"33a5710d5e96c5c0dcf3d05eb3f3a8f332cb592c0b332a3946eb932368f13780"},"schema_version":"1.0"},"canonical_sha256":"36849793bc5ea45d3effc3a17b4a48b50d9af7f11e1ab12b793c9ccfe076cd95","source":{"kind":"arxiv","id":"2305.18411","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.18411","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2305.18411v2","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.18411","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"G2CJPE54L2SF","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"G2CJPE54L2SF2PX7","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"G2CJPE54","created_at":"2026-07-05T07:20:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:G2CJPE54L2SF2PX7YOQXWSSIWU","target":"record","payload":{"canonical_record":{"source":{"id":"2305.18411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-28T17:09:32Z","cross_cats_sorted":[],"title_canon_sha256":"4c71c3c77365bb51c6481a163de7680e83a484e8f36fcda60ed285d1be092b49","abstract_canon_sha256":"33a5710d5e96c5c0dcf3d05eb3f3a8f332cb592c0b332a3946eb932368f13780"},"schema_version":"1.0"},"canonical_sha256":"36849793bc5ea45d3effc3a17b4a48b50d9af7f11e1ab12b793c9ccfe076cd95","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:20:51.487905Z","signature_b64":"dF6pBCXNwEfI6P5IyP+/i633bhuazxnAnjA/3PcLKiwsdmNZLjskUYAiw2cV1c7hnOg2GCSthPRpAussICMFCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36849793bc5ea45d3effc3a17b4a48b50d9af7f11e1ab12b793c9ccfe076cd95","last_reissued_at":"2026-07-05T07:20:51.487480Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:20:51.487480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.18411","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mhc7i5kOEyUNgLO/YWknVCJ9YeIi7rdhXUTMA13x2SGNw7nTYU2l4vPsrfDqQgyH3PoMEc7MUBLeZTGKYQ1MCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:03:20.301609Z"},"content_sha256":"d128fa4a61bbbbce97671de00910af93c451a29bf89e15124250d034c70f4689","schema_version":"1.0","event_id":"sha256:d128fa4a61bbbbce97671de00910af93c451a29bf89e15124250d034c70f4689"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:G2CJPE54L2SF2PX7YOQXWSSIWU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Feature-Learning Networks Are Consistent Across Widths At Realistic Scales","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan, Depen Morwani, Nikhil Vyas, Sabarish Sainathan","submitted_at":"2023-05-28T17:09:32Z","abstract_excerpt":"We study the effect of width on the dynamics of feature-learning neural networks across a variety of architectures and datasets. Early in training, wide neural networks trained on online data have not only identical loss curves but also agree in their point-wise test predictions throughout training. For simple tasks such as CIFAR-5m this holds throughout training for networks of realistic widths. We also show that structural properties of the models, including internal representations, preactivation distributions, edge of stability phenomena, and large learning rate effects are consistent acro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.18411","kind":"arxiv","version":2},"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/2305.18411/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":"2026-07-05T07:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zKIMQG6jLfWuV8SJ1bBN9kNlaRolx8UEXopkBxCGz4uE/+DEZN/n05uokA2ZhzI8/wawvK9MkpNrTpbVzFimAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:03:20.302177Z"},"content_sha256":"3fd000a8cf184b6164f5362b1fda03ee88c0808529494d79048c1c0b0237c5c5","schema_version":"1.0","event_id":"sha256:3fd000a8cf184b6164f5362b1fda03ee88c0808529494d79048c1c0b0237c5c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/bundle.json","state_url":"https://pith.science/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/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":"2026-08-09T13:03:20Z","links":{"resolver":"https://pith.science/pith/G2CJPE54L2SF2PX7YOQXWSSIWU","bundle":"https://pith.science/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/bundle.json","state":"https://pith.science/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G2CJPE54L2SF2PX7YOQXWSSIWU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:G2CJPE54L2SF2PX7YOQXWSSIWU","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":"33a5710d5e96c5c0dcf3d05eb3f3a8f332cb592c0b332a3946eb932368f13780","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-28T17:09:32Z","title_canon_sha256":"4c71c3c77365bb51c6481a163de7680e83a484e8f36fcda60ed285d1be092b49"},"schema_version":"1.0","source":{"id":"2305.18411","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.18411","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2305.18411v2","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.18411","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"G2CJPE54L2SF","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"G2CJPE54L2SF2PX7","created_at":"2026-07-05T07:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"G2CJPE54","created_at":"2026-07-05T07:20:51Z"}],"graph_snapshots":[{"event_id":"sha256:3fd000a8cf184b6164f5362b1fda03ee88c0808529494d79048c1c0b0237c5c5","target":"graph","created_at":"2026-07-05T07:20:51Z","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/2305.18411/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the effect of width on the dynamics of feature-learning neural networks across a variety of architectures and datasets. Early in training, wide neural networks trained on online data have not only identical loss curves but also agree in their point-wise test predictions throughout training. For simple tasks such as CIFAR-5m this holds throughout training for networks of realistic widths. We also show that structural properties of the models, including internal representations, preactivation distributions, edge of stability phenomena, and large learning rate effects are consistent acro","authors_text":"Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan, Depen Morwani, Nikhil Vyas, Sabarish Sainathan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-28T17:09:32Z","title":"Feature-Learning Networks Are Consistent Across Widths At Realistic Scales"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.18411","kind":"arxiv","version":2},"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:d128fa4a61bbbbce97671de00910af93c451a29bf89e15124250d034c70f4689","target":"record","created_at":"2026-07-05T07:20:51Z","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":"33a5710d5e96c5c0dcf3d05eb3f3a8f332cb592c0b332a3946eb932368f13780","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-28T17:09:32Z","title_canon_sha256":"4c71c3c77365bb51c6481a163de7680e83a484e8f36fcda60ed285d1be092b49"},"schema_version":"1.0","source":{"id":"2305.18411","kind":"arxiv","version":2}},"canonical_sha256":"36849793bc5ea45d3effc3a17b4a48b50d9af7f11e1ab12b793c9ccfe076cd95","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36849793bc5ea45d3effc3a17b4a48b50d9af7f11e1ab12b793c9ccfe076cd95","first_computed_at":"2026-07-05T07:20:51.487480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:20:51.487480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dF6pBCXNwEfI6P5IyP+/i633bhuazxnAnjA/3PcLKiwsdmNZLjskUYAiw2cV1c7hnOg2GCSthPRpAussICMFCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:20:51.487905Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.18411","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d128fa4a61bbbbce97671de00910af93c451a29bf89e15124250d034c70f4689","sha256:3fd000a8cf184b6164f5362b1fda03ee88c0808529494d79048c1c0b0237c5c5"],"state_sha256":"961fb812f5532c67a609277c7b83f6f8befd9f2e306c8f84681abae8518ab3bd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zz2wfnBa/wsrOsjdxN+rHpi8h17hJXw4MZ8LwPTKPY5nmn+/N5UdJo27KeDmjmifxmYjPIBLa7/Qe/cMaI48DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:03:20.305817Z","bundle_sha256":"3d6351bcbbdc5c39996be849c344cdaab0c4d0a917d40d7165a77cfe8562abd5"}}