{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ZVLHBC6EXN4T43CCBPU5WVYAT2","short_pith_number":"pith:ZVLHBC6E","canonical_record":{"source":{"id":"1901.10824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-30T13:44:08Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"36653a53af9e3139f23f68e741aec9164b05210c7c35caed65b84ee73634d3b8","abstract_canon_sha256":"a49d2322a5c960c07b818aad49499d578402b1e8ac9a4473ff71c5dff2b32590"},"schema_version":"1.0"},"canonical_sha256":"cd56708bc4bb793e6c420be9db57009ea0f6a976dfb8c03f2d82a69abb47fadf","source":{"kind":"arxiv","id":"1901.10824","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.10824","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"arxiv_version","alias_value":"1901.10824v1","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.10824","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"pith_short_12","alias_value":"ZVLHBC6EXN4T","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZVLHBC6EXN4T43CC","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZVLHBC6E","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ZVLHBC6EXN4T43CCBPU5WVYAT2","target":"record","payload":{"canonical_record":{"source":{"id":"1901.10824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-30T13:44:08Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"36653a53af9e3139f23f68e741aec9164b05210c7c35caed65b84ee73634d3b8","abstract_canon_sha256":"a49d2322a5c960c07b818aad49499d578402b1e8ac9a4473ff71c5dff2b32590"},"schema_version":"1.0"},"canonical_sha256":"cd56708bc4bb793e6c420be9db57009ea0f6a976dfb8c03f2d82a69abb47fadf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:05.919665Z","signature_b64":"FQ01Y5p11pTGI9wToybCNB8PUn9M125/2Ur4wN4/qyyF8E7HF3UN8Uo8abVXlnDyriWJBWVKwl4V1usAxd0jAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd56708bc4bb793e6c420be9db57009ea0f6a976dfb8c03f2d82a69abb47fadf","last_reissued_at":"2026-05-17T23:55:05.919132Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:05.919132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.10824","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":"2026-05-17T23:55:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wqNYbxOaV5QvIjiGI8jgYlVZ71o7mMosGcty9Dfphr5wJxgnE3CCVhrJYBdB+rujZsgmjmttop/Rk7i3Oow5AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T15:33:21.063235Z"},"content_sha256":"f6c5d6382e3c2677412e67c70fa4e6702a3c21077909d0c1dce7a119402f3376","schema_version":"1.0","event_id":"sha256:f6c5d6382e3c2677412e67c70fa4e6702a3c21077909d0c1dce7a119402f3376"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ZVLHBC6EXN4T43CCBPU5WVYAT2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diversity Regularized Adversarial Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Babajide O. Ayinde, Jacek M. Zurada, Keishin Nishihama","submitted_at":"2019-01-30T13:44:08Z","abstract_excerpt":"The two key players in Generative Adversarial Networks (GANs), the discriminator and generator, are usually parameterized as deep neural networks (DNNs). On many generative tasks, GANs achieve state-of-the-art performance but are often unstable to train and sometimes miss modes. A typical failure mode is the collapse of the generator to a single parameter configuration where its outputs are identical. When this collapse occurs, the gradient of the discriminator may point in similar directions for many similar points. We hypothesize that some of these shortcomings are in part due to primitive a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.10824","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":""},"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":"2026-05-17T23:55:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZKXKxpfCKNpFg/fhHj7X6tH4Bcssa7Mn7RNVaFSKcGyMySPENa+irfR0q3mVjzDxwddKSzEabg9Md24qI6GcDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T15:33:21.063598Z"},"content_sha256":"1925bd55cbb9e6135f412d1a272d104a662a0593afa0f4c5b2156e4c348ed23b","schema_version":"1.0","event_id":"sha256:1925bd55cbb9e6135f412d1a272d104a662a0593afa0f4c5b2156e4c348ed23b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/bundle.json","state_url":"https://pith.science/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/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":"2026-06-26T15:33:21Z","links":{"resolver":"https://pith.science/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2","bundle":"https://pith.science/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/bundle.json","state":"https://pith.science/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZVLHBC6EXN4T43CCBPU5WVYAT2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZVLHBC6EXN4T43CCBPU5WVYAT2","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":"a49d2322a5c960c07b818aad49499d578402b1e8ac9a4473ff71c5dff2b32590","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-30T13:44:08Z","title_canon_sha256":"36653a53af9e3139f23f68e741aec9164b05210c7c35caed65b84ee73634d3b8"},"schema_version":"1.0","source":{"id":"1901.10824","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.10824","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"arxiv_version","alias_value":"1901.10824v1","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.10824","created_at":"2026-05-17T23:55:05Z"},{"alias_kind":"pith_short_12","alias_value":"ZVLHBC6EXN4T","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZVLHBC6EXN4T43CC","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZVLHBC6E","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:1925bd55cbb9e6135f412d1a272d104a662a0593afa0f4c5b2156e4c348ed23b","target":"graph","created_at":"2026-05-17T23:55:05Z","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":"The two key players in Generative Adversarial Networks (GANs), the discriminator and generator, are usually parameterized as deep neural networks (DNNs). On many generative tasks, GANs achieve state-of-the-art performance but are often unstable to train and sometimes miss modes. A typical failure mode is the collapse of the generator to a single parameter configuration where its outputs are identical. When this collapse occurs, the gradient of the discriminator may point in similar directions for many similar points. We hypothesize that some of these shortcomings are in part due to primitive a","authors_text":"Babajide O. Ayinde, Jacek M. Zurada, Keishin Nishihama","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-30T13:44:08Z","title":"Diversity Regularized Adversarial Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.10824","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:f6c5d6382e3c2677412e67c70fa4e6702a3c21077909d0c1dce7a119402f3376","target":"record","created_at":"2026-05-17T23:55:05Z","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":"a49d2322a5c960c07b818aad49499d578402b1e8ac9a4473ff71c5dff2b32590","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-30T13:44:08Z","title_canon_sha256":"36653a53af9e3139f23f68e741aec9164b05210c7c35caed65b84ee73634d3b8"},"schema_version":"1.0","source":{"id":"1901.10824","kind":"arxiv","version":1}},"canonical_sha256":"cd56708bc4bb793e6c420be9db57009ea0f6a976dfb8c03f2d82a69abb47fadf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd56708bc4bb793e6c420be9db57009ea0f6a976dfb8c03f2d82a69abb47fadf","first_computed_at":"2026-05-17T23:55:05.919132Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:55:05.919132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FQ01Y5p11pTGI9wToybCNB8PUn9M125/2Ur4wN4/qyyF8E7HF3UN8Uo8abVXlnDyriWJBWVKwl4V1usAxd0jAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:55:05.919665Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.10824","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f6c5d6382e3c2677412e67c70fa4e6702a3c21077909d0c1dce7a119402f3376","sha256:1925bd55cbb9e6135f412d1a272d104a662a0593afa0f4c5b2156e4c348ed23b"],"state_sha256":"fa9e1d44c664d7e9e1d695c7f8eab1b093bea6f9f5cd16e660cf7dcba2456668"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lucWnq9PdmFGnuOJcpvmQAWCLFD5aAT70ekCz3dsW62vlKErGCoknss4hz6nbqG8oaHQQkHs19mqgx4mvBtbCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T15:33:21.065548Z","bundle_sha256":"6d866b65a9e0cd36de02f46b717b86e596e127964ca814135708ee73987d8ecd"}}