{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZIIZQ5WT6KQ4L5WKREYVS3VN4V","short_pith_number":"pith:ZIIZQ5WT","canonical_record":{"source":{"id":"2409.05782","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-09T16:45:26Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"719a03dba604e28d454aaf9b561f044d40209d6d3a78e013770c65fe03acd841","abstract_canon_sha256":"141ef68745229a345d618f3497b7c5d664576d776acedaabee9cd784c5f6d418"},"schema_version":"1.0"},"canonical_sha256":"ca119876d3f2a1c5f6ca8931596eade5686761e99684566d9aeca1ad83962cfd","source":{"kind":"arxiv","id":"2409.05782","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.05782","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"arxiv_version","alias_value":"2409.05782v1","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.05782","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZIIZQ5WT6KQ4","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_16","alias_value":"ZIIZQ5WT6KQ4L5WK","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_8","alias_value":"ZIIZQ5WT","created_at":"2026-07-05T09:04:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZIIZQ5WT6KQ4L5WKREYVS3VN4V","target":"record","payload":{"canonical_record":{"source":{"id":"2409.05782","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-09T16:45:26Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"719a03dba604e28d454aaf9b561f044d40209d6d3a78e013770c65fe03acd841","abstract_canon_sha256":"141ef68745229a345d618f3497b7c5d664576d776acedaabee9cd784c5f6d418"},"schema_version":"1.0"},"canonical_sha256":"ca119876d3f2a1c5f6ca8931596eade5686761e99684566d9aeca1ad83962cfd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:04:54.027180Z","signature_b64":"qZS9b3FrIyXfTwkQPSHXHfrqA4QE1ktxcB9ZXfbSiQLOC40wTy83vHit6lkEJstYIZKM9YjUkhBucrs3jMLWDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ca119876d3f2a1c5f6ca8931596eade5686761e99684566d9aeca1ad83962cfd","last_reissued_at":"2026-07-05T09:04:54.026802Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:04:54.026802Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.05782","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:04:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XB9pbLN02BkWv7HkPL5EYDd2scBnWuVWiWlEmexwF3PJOd5LnlETtx4/3tPUMYv7D5rvElVaSnVi9HeFIUWlDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:09:00.555702Z"},"content_sha256":"cca841ecff035dd96c4dab078803eaeaa5bdeff0b9350d2becea6b30a8a15175","schema_version":"1.0","event_id":"sha256:cca841ecff035dd96c4dab078803eaeaa5bdeff0b9350d2becea6b30a8a15175"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZIIZQ5WT6KQ4L5WKREYVS3VN4V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unified Neural Network Scaling Laws and Scale-time Equivalence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Akhilan Boopathy, Ila Fiete","submitted_at":"2024-09-09T16:45:26Z","abstract_excerpt":"As neural networks continue to grow in size but datasets might not, it is vital to understand how much performance improvement can be expected: is it more important to scale network size or data volume? Thus, neural network scaling laws, which characterize how test error varies with network size and data volume, have become increasingly important. However, existing scaling laws are often applicable only in limited regimes and often do not incorporate or predict well-known phenomena such as double descent. Here, we present a novel theoretical characterization of how three factors -- model size,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.05782","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.05782/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":"2026-07-05T09:04:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4oM3Unn/vfnMYznQsibSdSdT7FFUqfrGWbF7iGX8lUAXrdsdGiwSlycBJY/HNjzMTnM3Dgh7ORsu6k4K//g2CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:09:00.556373Z"},"content_sha256":"b625bf5862133df9b9e5d1992c796b9ff0824dd30721052d3d64ccae32d9f38e","schema_version":"1.0","event_id":"sha256:b625bf5862133df9b9e5d1992c796b9ff0824dd30721052d3d64ccae32d9f38e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/bundle.json","state_url":"https://pith.science/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/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":"2026-08-06T19:09:00Z","links":{"resolver":"https://pith.science/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V","bundle":"https://pith.science/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/bundle.json","state":"https://pith.science/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZIIZQ5WT6KQ4L5WKREYVS3VN4V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZIIZQ5WT6KQ4L5WKREYVS3VN4V","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":"141ef68745229a345d618f3497b7c5d664576d776acedaabee9cd784c5f6d418","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-09T16:45:26Z","title_canon_sha256":"719a03dba604e28d454aaf9b561f044d40209d6d3a78e013770c65fe03acd841"},"schema_version":"1.0","source":{"id":"2409.05782","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.05782","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"arxiv_version","alias_value":"2409.05782v1","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.05782","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZIIZQ5WT6KQ4","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_16","alias_value":"ZIIZQ5WT6KQ4L5WK","created_at":"2026-07-05T09:04:54Z"},{"alias_kind":"pith_short_8","alias_value":"ZIIZQ5WT","created_at":"2026-07-05T09:04:54Z"}],"graph_snapshots":[{"event_id":"sha256:b625bf5862133df9b9e5d1992c796b9ff0824dd30721052d3d64ccae32d9f38e","target":"graph","created_at":"2026-07-05T09:04:54Z","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/2409.05782/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As neural networks continue to grow in size but datasets might not, it is vital to understand how much performance improvement can be expected: is it more important to scale network size or data volume? Thus, neural network scaling laws, which characterize how test error varies with network size and data volume, have become increasingly important. However, existing scaling laws are often applicable only in limited regimes and often do not incorporate or predict well-known phenomena such as double descent. Here, we present a novel theoretical characterization of how three factors -- model size,","authors_text":"Akhilan Boopathy, Ila Fiete","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-09T16:45:26Z","title":"Unified Neural Network Scaling Laws and Scale-time Equivalence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.05782","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:cca841ecff035dd96c4dab078803eaeaa5bdeff0b9350d2becea6b30a8a15175","target":"record","created_at":"2026-07-05T09:04:54Z","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":"141ef68745229a345d618f3497b7c5d664576d776acedaabee9cd784c5f6d418","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-09T16:45:26Z","title_canon_sha256":"719a03dba604e28d454aaf9b561f044d40209d6d3a78e013770c65fe03acd841"},"schema_version":"1.0","source":{"id":"2409.05782","kind":"arxiv","version":1}},"canonical_sha256":"ca119876d3f2a1c5f6ca8931596eade5686761e99684566d9aeca1ad83962cfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca119876d3f2a1c5f6ca8931596eade5686761e99684566d9aeca1ad83962cfd","first_computed_at":"2026-07-05T09:04:54.026802Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:04:54.026802Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qZS9b3FrIyXfTwkQPSHXHfrqA4QE1ktxcB9ZXfbSiQLOC40wTy83vHit6lkEJstYIZKM9YjUkhBucrs3jMLWDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:04:54.027180Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.05782","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cca841ecff035dd96c4dab078803eaeaa5bdeff0b9350d2becea6b30a8a15175","sha256:b625bf5862133df9b9e5d1992c796b9ff0824dd30721052d3d64ccae32d9f38e"],"state_sha256":"a72486e03b96f730ebc4c75f72a9b67eeed540c761b35acbdbd1b5c54cdf8506"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/AsKyN0+jfzhoWBYQ2Du4YkUQSXKUe5APmqRlqD2H+CEKTFigpF92zvMcE4SMACAa3iBdaYeAO7kQ8Eab9wrAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:09:00.563948Z","bundle_sha256":"362c39533444daa855aa4000a51c2bf7d6f978bd555485d425cb232fbc5aa624"}}