{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HSMOSGIJQEHBXXF6HBY5L6TH6S","short_pith_number":"pith:HSMOSGIJ","canonical_record":{"source":{"id":"1709.06548","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-19T17:50:40Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"1a404ef769d7c12ffa09d8d12628f66838b989d68d0a46ca946efc46b8f35342","abstract_canon_sha256":"16a18f07648ebfd3ef8b1ce34ccf2caea3e0023fefee17c5158f76fc6730f391"},"schema_version":"1.0"},"canonical_sha256":"3c98e91909810e1bdcbe3871d5fa67f4adcf246f3ff0a0b638955fb6f88b6292","source":{"kind":"arxiv","id":"1709.06548","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06548","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06548v2","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06548","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"HSMOSGIJQEHB","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HSMOSGIJQEHBXXF6","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HSMOSGIJ","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HSMOSGIJQEHBXXF6HBY5L6TH6S","target":"record","payload":{"canonical_record":{"source":{"id":"1709.06548","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-19T17:50:40Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"1a404ef769d7c12ffa09d8d12628f66838b989d68d0a46ca946efc46b8f35342","abstract_canon_sha256":"16a18f07648ebfd3ef8b1ce34ccf2caea3e0023fefee17c5158f76fc6730f391"},"schema_version":"1.0"},"canonical_sha256":"3c98e91909810e1bdcbe3871d5fa67f4adcf246f3ff0a0b638955fb6f88b6292","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:16.364383Z","signature_b64":"rgZxpyQWYQLQgDX9Qtlw4EFhWCo4aIjw5dx2qfz6e/76+aG2Ur8fvW1ehFvXNj3X1NfAp/UMhXDcArJKnYWGAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c98e91909810e1bdcbe3871d5fa67f4adcf246f3ff0a0b638955fb6f88b6292","last_reissued_at":"2026-05-18T00:30:16.363636Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:16.363636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.06548","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":"2026-05-18T00:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ftktmHie5vXUbkC85OyohfWkOB648875PU6SN9856JyEUTOx8/vrZ2lB2v27MEDESwVK/Hk8zI0Uy4m4JRN0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T21:22:12.671586Z"},"content_sha256":"88a0e2a389171632f0efa8aad1ed6fda0c392fa5da5a98248b2e33cdb62b5de5","schema_version":"1.0","event_id":"sha256:88a0e2a389171632f0efa8aad1ed6fda0c392fa5da5a98248b2e33cdb62b5de5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HSMOSGIJQEHBXXF6HBY5L6TH6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Triangle Generative Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chunyuan Li, Hao Liu, Lawrence Carin, Liqun Chen, Weiyao Wang, Yizhe Zhang, Yunchen Pu, Zhe Gan","submitted_at":"2017-09-19T17:50:40Z","abstract_excerpt":"A Triangle Generative Adversarial Network ($\\Delta$-GAN) is developed for semi-supervised cross-domain joint distribution matching, where the training data consists of samples from each domain, and supervision of domain correspondence is provided by only a few paired samples. $\\Delta$-GAN consists of four neural networks, two generators and two discriminators. The generators are designed to learn the two-way conditional distributions between the two domains, while the discriminators implicitly define a ternary discriminative function, which is trained to distinguish real data pairs and two kin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06548","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":""},"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":"2026-05-18T00:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zRKweG9mcVWMDpNTnizT/VLWaEq05fNjk2meKvT1115uDGeHDLTalG7jbJZZ3jVIYTIoJJSBmVDe9pD4z2KhDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T21:22:12.672398Z"},"content_sha256":"889357438b6143c957ee0f8820385cd359da86d770c6746effd2c6f4a013ddb1","schema_version":"1.0","event_id":"sha256:889357438b6143c957ee0f8820385cd359da86d770c6746effd2c6f4a013ddb1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/bundle.json","state_url":"https://pith.science/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/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":"2026-05-18T21:22:12Z","links":{"resolver":"https://pith.science/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S","bundle":"https://pith.science/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/bundle.json","state":"https://pith.science/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HSMOSGIJQEHBXXF6HBY5L6TH6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HSMOSGIJQEHBXXF6HBY5L6TH6S","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":"16a18f07648ebfd3ef8b1ce34ccf2caea3e0023fefee17c5158f76fc6730f391","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-19T17:50:40Z","title_canon_sha256":"1a404ef769d7c12ffa09d8d12628f66838b989d68d0a46ca946efc46b8f35342"},"schema_version":"1.0","source":{"id":"1709.06548","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06548","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06548v2","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06548","created_at":"2026-05-18T00:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"HSMOSGIJQEHB","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HSMOSGIJQEHBXXF6","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HSMOSGIJ","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:889357438b6143c957ee0f8820385cd359da86d770c6746effd2c6f4a013ddb1","target":"graph","created_at":"2026-05-18T00:30:16Z","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":"A Triangle Generative Adversarial Network ($\\Delta$-GAN) is developed for semi-supervised cross-domain joint distribution matching, where the training data consists of samples from each domain, and supervision of domain correspondence is provided by only a few paired samples. $\\Delta$-GAN consists of four neural networks, two generators and two discriminators. The generators are designed to learn the two-way conditional distributions between the two domains, while the discriminators implicitly define a ternary discriminative function, which is trained to distinguish real data pairs and two kin","authors_text":"Chunyuan Li, Hao Liu, Lawrence Carin, Liqun Chen, Weiyao Wang, Yizhe Zhang, Yunchen Pu, Zhe Gan","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-19T17:50:40Z","title":"Triangle Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06548","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":"sha256:88a0e2a389171632f0efa8aad1ed6fda0c392fa5da5a98248b2e33cdb62b5de5","target":"record","created_at":"2026-05-18T00:30:16Z","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":"16a18f07648ebfd3ef8b1ce34ccf2caea3e0023fefee17c5158f76fc6730f391","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-19T17:50:40Z","title_canon_sha256":"1a404ef769d7c12ffa09d8d12628f66838b989d68d0a46ca946efc46b8f35342"},"schema_version":"1.0","source":{"id":"1709.06548","kind":"arxiv","version":2}},"canonical_sha256":"3c98e91909810e1bdcbe3871d5fa67f4adcf246f3ff0a0b638955fb6f88b6292","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c98e91909810e1bdcbe3871d5fa67f4adcf246f3ff0a0b638955fb6f88b6292","first_computed_at":"2026-05-18T00:30:16.363636Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:30:16.363636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rgZxpyQWYQLQgDX9Qtlw4EFhWCo4aIjw5dx2qfz6e/76+aG2Ur8fvW1ehFvXNj3X1NfAp/UMhXDcArJKnYWGAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:30:16.364383Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.06548","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88a0e2a389171632f0efa8aad1ed6fda0c392fa5da5a98248b2e33cdb62b5de5","sha256:889357438b6143c957ee0f8820385cd359da86d770c6746effd2c6f4a013ddb1"],"state_sha256":"3223435ae55a72cefe67f17f9fff3399b2feed3b3340dd645ef8f3411da0eb4d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HAGdd2dIS/g2z8qCPCTv3WJjH+MzaTAPQv/5RRiiWpxppc3ahJfgeCsgz54EHg1mbOyOZ43Xd0m32JrkrZBZDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-18T21:22:12.674565Z","bundle_sha256":"93e093c6404a41701efad9daa3428de84e5387c50789356938bfc15f1be664ed"}}