{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:SSF6TL6VSW7HBM2UI7Z34VFBPQ","short_pith_number":"pith:SSF6TL6V","canonical_record":{"source":{"id":"1803.05859","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-03-15T16:54:43Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"df8d736b1428f9b68472a2cae3cc571f4df980d4a71bb97d0b7e0607d141714f","abstract_canon_sha256":"533c7d1e604165103989752bac758d28e31baa221f6458a2c60bc410e7a480bb"},"schema_version":"1.0"},"canonical_sha256":"948be9afd595be70b35447f3be54a17c05ba2a68c59062e6b81066b0c50ce696","source":{"kind":"arxiv","id":"1803.05859","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.05859","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"arxiv_version","alias_value":"1803.05859v4","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.05859","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"pith_short_12","alias_value":"SSF6TL6VSW7H","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SSF6TL6VSW7HBM2U","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SSF6TL6V","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:SSF6TL6VSW7HBM2UI7Z34VFBPQ","target":"record","payload":{"canonical_record":{"source":{"id":"1803.05859","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-03-15T16:54:43Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"df8d736b1428f9b68472a2cae3cc571f4df980d4a71bb97d0b7e0607d141714f","abstract_canon_sha256":"533c7d1e604165103989752bac758d28e31baa221f6458a2c60bc410e7a480bb"},"schema_version":"1.0"},"canonical_sha256":"948be9afd595be70b35447f3be54a17c05ba2a68c59062e6b81066b0c50ce696","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:59.383698Z","signature_b64":"Kb0Knlax5Jd3og9H93D7WICdaYkQfDLW8bWmaTibrqLBGHR+27HxLUHYiIUIGz2TgaKB0D4mVzyiVWniBmSsCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"948be9afd595be70b35447f3be54a17c05ba2a68c59062e6b81066b0c50ce696","last_reissued_at":"2026-05-18T00:14:59.383042Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:59.383042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.05859","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hx7KbGP/Ex/bn38Fvg/ZbOjs5XGrpO8LPUFqy7hN1gunzjrWjKkTVfUqGZ37F+T46sU+JetQIyeHIQUVEReoBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T10:58:34.029183Z"},"content_sha256":"3583817f7324fd260e5690871ce52c18dbddab647203204161014aaa72bfb5b3","schema_version":"1.0","event_id":"sha256:3583817f7324fd260e5690871ce52c18dbddab647203204161014aaa72bfb5b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:SSF6TL6VSW7HBM2UI7Z34VFBPQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Network Quine","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.AI","authors_text":"Hod Lipson, Oscar Chang","submitted_at":"2018-03-15T16:54:43Z","abstract_excerpt":"Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems. Here we describe how to build and train self-replicating neural networks. The network replicates itself by learning to output its own weights. The network is designed using a loss function that can be optimized with either gradient-based or non-gradient-based methods. We also describe a method we call regeneration to train the network without explicit optimization, by injecting the network with predictions of its own parameters. The best solution for a self-replicating netwo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.05859","kind":"arxiv","version":4},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rocsnr134wei4BhrN4uPKvAOh1ZjYSi+eq4dcQwHVJtBrq11vXEp3HEBTHEabDTlj/rg3dv4PMVyfQEVD4qdDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T10:58:34.029550Z"},"content_sha256":"c061a7a8f4f72930e88c2fe7592fe398bd7a7c795a1aac12c14af01dae375fda","schema_version":"1.0","event_id":"sha256:c061a7a8f4f72930e88c2fe7592fe398bd7a7c795a1aac12c14af01dae375fda"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/bundle.json","state_url":"https://pith.science/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/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":"2026-05-26T10:58:34Z","links":{"resolver":"https://pith.science/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ","bundle":"https://pith.science/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/bundle.json","state":"https://pith.science/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SSF6TL6VSW7HBM2UI7Z34VFBPQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SSF6TL6VSW7HBM2UI7Z34VFBPQ","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":"533c7d1e604165103989752bac758d28e31baa221f6458a2c60bc410e7a480bb","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-03-15T16:54:43Z","title_canon_sha256":"df8d736b1428f9b68472a2cae3cc571f4df980d4a71bb97d0b7e0607d141714f"},"schema_version":"1.0","source":{"id":"1803.05859","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.05859","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"arxiv_version","alias_value":"1803.05859v4","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.05859","created_at":"2026-05-18T00:14:59Z"},{"alias_kind":"pith_short_12","alias_value":"SSF6TL6VSW7H","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SSF6TL6VSW7HBM2U","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SSF6TL6V","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:c061a7a8f4f72930e88c2fe7592fe398bd7a7c795a1aac12c14af01dae375fda","target":"graph","created_at":"2026-05-18T00:14:59Z","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"},"paper":{"abstract_excerpt":"Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems. Here we describe how to build and train self-replicating neural networks. The network replicates itself by learning to output its own weights. The network is designed using a loss function that can be optimized with either gradient-based or non-gradient-based methods. We also describe a method we call regeneration to train the network without explicit optimization, by injecting the network with predictions of its own parameters. The best solution for a self-replicating netwo","authors_text":"Hod Lipson, Oscar Chang","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-03-15T16:54:43Z","title":"Neural Network Quine"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.05859","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":"sha256:3583817f7324fd260e5690871ce52c18dbddab647203204161014aaa72bfb5b3","target":"record","created_at":"2026-05-18T00:14:59Z","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":"533c7d1e604165103989752bac758d28e31baa221f6458a2c60bc410e7a480bb","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-03-15T16:54:43Z","title_canon_sha256":"df8d736b1428f9b68472a2cae3cc571f4df980d4a71bb97d0b7e0607d141714f"},"schema_version":"1.0","source":{"id":"1803.05859","kind":"arxiv","version":4}},"canonical_sha256":"948be9afd595be70b35447f3be54a17c05ba2a68c59062e6b81066b0c50ce696","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"948be9afd595be70b35447f3be54a17c05ba2a68c59062e6b81066b0c50ce696","first_computed_at":"2026-05-18T00:14:59.383042Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:59.383042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kb0Knlax5Jd3og9H93D7WICdaYkQfDLW8bWmaTibrqLBGHR+27HxLUHYiIUIGz2TgaKB0D4mVzyiVWniBmSsCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:59.383698Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.05859","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3583817f7324fd260e5690871ce52c18dbddab647203204161014aaa72bfb5b3","sha256:c061a7a8f4f72930e88c2fe7592fe398bd7a7c795a1aac12c14af01dae375fda"],"state_sha256":"c2684ace09818db1125bb42466bcc5c73fd19cb33b026eb7f6108ec5c05d7f84"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p8ptXBjATZfznask+fBCQfr/8osTrkqZB9aXtyM9RmTQ6WrbOhMuEE8VuuBXG2HL4UEawxhZLnIEeQIHmCJxDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T10:58:34.032015Z","bundle_sha256":"34596dfef7db5c4c79a1b0da6a585097d4338ddfa7def402423acf63fdd9ef33"}}