{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:XEU6YNWZMTOJDB77PWOIACOC3W","short_pith_number":"pith:XEU6YNWZ","canonical_record":{"source":{"id":"1511.07543","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-24T02:31:46Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"23f1883f077c94d2d66db59e260f1516db3a5a7f2518eb0446ab04eb0a04de7b","abstract_canon_sha256":"f7fb6eb2d5fdcf33b3d375097f24e71a24601e5fa9299e287f7131c16bc0cb89"},"schema_version":"1.0"},"canonical_sha256":"b929ec36d964dc9187ff7d9c8009c2dd809fce24e24680b9c1323b9cf2accde4","source":{"kind":"arxiv","id":"1511.07543","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.07543","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"arxiv_version","alias_value":"1511.07543v3","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.07543","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"pith_short_12","alias_value":"XEU6YNWZMTOJ","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"XEU6YNWZMTOJDB77","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"XEU6YNWZ","created_at":"2026-05-18T12:29:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:XEU6YNWZMTOJDB77PWOIACOC3W","target":"record","payload":{"canonical_record":{"source":{"id":"1511.07543","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-24T02:31:46Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"23f1883f077c94d2d66db59e260f1516db3a5a7f2518eb0446ab04eb0a04de7b","abstract_canon_sha256":"f7fb6eb2d5fdcf33b3d375097f24e71a24601e5fa9299e287f7131c16bc0cb89"},"schema_version":"1.0"},"canonical_sha256":"b929ec36d964dc9187ff7d9c8009c2dd809fce24e24680b9c1323b9cf2accde4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:19:53.369522Z","signature_b64":"YgTJZXeGdsGUwdR5VeHH9Qf5y9uuDK34LU2dpiCywjYrrE7SdCjFJv45LOBCvj7oD7xoPZ/PcsEXFKWguxPUDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b929ec36d964dc9187ff7d9c8009c2dd809fce24e24680b9c1323b9cf2accde4","last_reissued_at":"2026-05-18T01:19:53.368876Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:19:53.368876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.07543","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":"2026-05-18T01:19:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x+rEaru0VjYrkgmeO7euC/iAB4NWGb5rKGxxZ9LRD7YWmf4+pey+gca9nydGugIFEjyozON7wiuKClNE1tO9Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T22:27:35.028335Z"},"content_sha256":"03fbc654146032c408aff283983c6d7f8fff65f0091b470d9bbb07a079cd2d2c","schema_version":"1.0","event_id":"sha256:03fbc654146032c408aff283983c6d7f8fff65f0091b470d9bbb07a079cd2d2c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:XEU6YNWZMTOJDB77PWOIACOC3W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Convergent Learning: Do different neural networks learn the same representations?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Hod Lipson, Jason Yosinski, Jeff Clune, John Hopcroft, Yixuan Li","submitted_at":"2015-11-24T02:31:46Z","abstract_excerpt":"Recent success in training deep neural networks have prompted active investigation into the features learned on their intermediate layers. Such research is difficult because it requires making sense of non-linear computations performed by millions of parameters, but valuable because it increases our ability to understand current models and create improved versions of them. In this paper we investigate the extent to which neural networks exhibit what we call convergent learning, which is when the representations learned by multiple nets converge to a set of features which are either individuall"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.07543","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":""},"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":"2026-05-18T01:19:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bxYowyOw4NDRo2JnU5hZ+8Fzg0KkPiIT7M20vt7Q3m46YqO82bAAT0LL3qtPTHcfP8EROPj5cLoK2rZxvz32AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T22:27:35.029128Z"},"content_sha256":"03147cdf4d1cf979646e5b00506c332abb6b0ae331e9a53b267a32f98358a466","schema_version":"1.0","event_id":"sha256:03147cdf4d1cf979646e5b00506c332abb6b0ae331e9a53b267a32f98358a466"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XEU6YNWZMTOJDB77PWOIACOC3W/bundle.json","state_url":"https://pith.science/pith/XEU6YNWZMTOJDB77PWOIACOC3W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XEU6YNWZMTOJDB77PWOIACOC3W/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":"2026-05-31T22:27:35Z","links":{"resolver":"https://pith.science/pith/XEU6YNWZMTOJDB77PWOIACOC3W","bundle":"https://pith.science/pith/XEU6YNWZMTOJDB77PWOIACOC3W/bundle.json","state":"https://pith.science/pith/XEU6YNWZMTOJDB77PWOIACOC3W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XEU6YNWZMTOJDB77PWOIACOC3W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:XEU6YNWZMTOJDB77PWOIACOC3W","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":"f7fb6eb2d5fdcf33b3d375097f24e71a24601e5fa9299e287f7131c16bc0cb89","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-24T02:31:46Z","title_canon_sha256":"23f1883f077c94d2d66db59e260f1516db3a5a7f2518eb0446ab04eb0a04de7b"},"schema_version":"1.0","source":{"id":"1511.07543","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.07543","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"arxiv_version","alias_value":"1511.07543v3","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.07543","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"pith_short_12","alias_value":"XEU6YNWZMTOJ","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"XEU6YNWZMTOJDB77","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"XEU6YNWZ","created_at":"2026-05-18T12:29:50Z"}],"graph_snapshots":[{"event_id":"sha256:03147cdf4d1cf979646e5b00506c332abb6b0ae331e9a53b267a32f98358a466","target":"graph","created_at":"2026-05-18T01:19:53Z","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":"Recent success in training deep neural networks have prompted active investigation into the features learned on their intermediate layers. Such research is difficult because it requires making sense of non-linear computations performed by millions of parameters, but valuable because it increases our ability to understand current models and create improved versions of them. In this paper we investigate the extent to which neural networks exhibit what we call convergent learning, which is when the representations learned by multiple nets converge to a set of features which are either individuall","authors_text":"Hod Lipson, Jason Yosinski, Jeff Clune, John Hopcroft, Yixuan Li","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-24T02:31:46Z","title":"Convergent Learning: Do different neural networks learn the same representations?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.07543","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":"sha256:03fbc654146032c408aff283983c6d7f8fff65f0091b470d9bbb07a079cd2d2c","target":"record","created_at":"2026-05-18T01:19:53Z","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":"f7fb6eb2d5fdcf33b3d375097f24e71a24601e5fa9299e287f7131c16bc0cb89","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-24T02:31:46Z","title_canon_sha256":"23f1883f077c94d2d66db59e260f1516db3a5a7f2518eb0446ab04eb0a04de7b"},"schema_version":"1.0","source":{"id":"1511.07543","kind":"arxiv","version":3}},"canonical_sha256":"b929ec36d964dc9187ff7d9c8009c2dd809fce24e24680b9c1323b9cf2accde4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b929ec36d964dc9187ff7d9c8009c2dd809fce24e24680b9c1323b9cf2accde4","first_computed_at":"2026-05-18T01:19:53.368876Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:19:53.368876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YgTJZXeGdsGUwdR5VeHH9Qf5y9uuDK34LU2dpiCywjYrrE7SdCjFJv45LOBCvj7oD7xoPZ/PcsEXFKWguxPUDA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:19:53.369522Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.07543","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:03fbc654146032c408aff283983c6d7f8fff65f0091b470d9bbb07a079cd2d2c","sha256:03147cdf4d1cf979646e5b00506c332abb6b0ae331e9a53b267a32f98358a466"],"state_sha256":"e1de8de0759d5ce50e4996e630cb65d561c58bb65e1f37c67a9561e9fab921ad"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iEMj2iAEWms8aqEiE6ZLl41cTLPC8lFdllhkNbty+zE6ZVLKLaROpYX32vZFwGRcpSuhghewL4hWtLE607AkCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T22:27:35.033793Z","bundle_sha256":"c2064cb259c88b617049896f387b53cc30e8917efcd7817732d074abe0df18c0"}}