{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:2LGJ7SJVAAXG3GBXTGNE32U7ZL","short_pith_number":"pith:2LGJ7SJV","canonical_record":{"source":{"id":"1802.10151","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-27T20:29:20Z","cross_cats_sorted":[],"title_canon_sha256":"ac0698e98ec5e56128c9dd0acc41dfd92b83dc8b3558b98528a9fd2ffc1dfe3b","abstract_canon_sha256":"99efb8731e890a593daba686bb6a56b826383bfc3a012c4b1bf0da1176baa590"},"schema_version":"1.0"},"canonical_sha256":"d2cc9fc935002e6d9837999a4dea9fcac8ff356ee1eac7ed214c76375e35eb3e","source":{"kind":"arxiv","id":"1802.10151","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10151","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10151v2","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10151","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"pith_short_12","alias_value":"2LGJ7SJVAAXG","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2LGJ7SJVAAXG3GBX","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2LGJ7SJV","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:2LGJ7SJVAAXG3GBXTGNE32U7ZL","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10151","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-27T20:29:20Z","cross_cats_sorted":[],"title_canon_sha256":"ac0698e98ec5e56128c9dd0acc41dfd92b83dc8b3558b98528a9fd2ffc1dfe3b","abstract_canon_sha256":"99efb8731e890a593daba686bb6a56b826383bfc3a012c4b1bf0da1176baa590"},"schema_version":"1.0"},"canonical_sha256":"d2cc9fc935002e6d9837999a4dea9fcac8ff356ee1eac7ed214c76375e35eb3e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:12:58.480489Z","signature_b64":"9GEHkWNCfWUIJApZpmoZmfYgR5ZeWMPZZnEhUNiFx/6VIrfT4xX0w48O/emsTqn4WtwXAMZymURzDn4bKbu0DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d2cc9fc935002e6d9837999a4dea9fcac8ff356ee1eac7ed214c76375e35eb3e","last_reissued_at":"2026-05-18T00:12:58.479978Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:12:58.479978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10151","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":"2026-05-18T00:12:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bWMwT29po2FSmTd0CQseZaOgalkaYPlJQvNY43+P8v8QSx9oH2gz1RHTyoAKYzirGw680f/iE2TdBTnA1UPbCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T15:35:38.805492Z"},"content_sha256":"2925aff1905ba9929d17e2b8898ed4010720a885fc9341cfde1519613a8597e2","schema_version":"1.0","event_id":"sha256:2925aff1905ba9929d17e2b8898ed4010720a885fc9341cfde1519613a8597e2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:2LGJ7SJVAAXG3GBXTGNE32U7ZL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Aaron Courville, Alessandro Sordoni, Amjad Almahairi, Philip Bachman, Sai Rajeswar","submitted_at":"2018-02-27T20:29:20Z","abstract_excerpt":"Learning inter-domain mappings from unpaired data can improve performance in structured prediction tasks, such as image segmentation, by reducing the need for paired data. CycleGAN was recently proposed for this problem, but critically assumes the underlying inter-domain mapping is approximately deterministic and one-to-one. This assumption renders the model ineffective for tasks requiring flexible, many-to-many mappings. We propose a new model, called Augmented CycleGAN, which learns many-to-many mappings between domains. We examine Augmented CycleGAN qualitatively and quantitatively on sever"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10151","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":"2026-05-18T00:12:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QnIGT7Vx4dP0k+neY03Xg60KswYAfgNSn46Vn3D3bwm5keKXVy7fuZ6KHK0VpTs3XouTQaDa+dap7eeaqGqBCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T15:35:38.806233Z"},"content_sha256":"c9026a3778d34b4f7c9f8017b75cec29c26ba95f56ed32e5710211e2b7e79e9e","schema_version":"1.0","event_id":"sha256:c9026a3778d34b4f7c9f8017b75cec29c26ba95f56ed32e5710211e2b7e79e9e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/bundle.json","state_url":"https://pith.science/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/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":"2026-05-28T15:35:38Z","links":{"resolver":"https://pith.science/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL","bundle":"https://pith.science/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/bundle.json","state":"https://pith.science/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2LGJ7SJVAAXG3GBXTGNE32U7ZL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:2LGJ7SJVAAXG3GBXTGNE32U7ZL","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":"99efb8731e890a593daba686bb6a56b826383bfc3a012c4b1bf0da1176baa590","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-27T20:29:20Z","title_canon_sha256":"ac0698e98ec5e56128c9dd0acc41dfd92b83dc8b3558b98528a9fd2ffc1dfe3b"},"schema_version":"1.0","source":{"id":"1802.10151","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10151","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10151v2","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10151","created_at":"2026-05-18T00:12:58Z"},{"alias_kind":"pith_short_12","alias_value":"2LGJ7SJVAAXG","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2LGJ7SJVAAXG3GBX","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2LGJ7SJV","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:c9026a3778d34b4f7c9f8017b75cec29c26ba95f56ed32e5710211e2b7e79e9e","target":"graph","created_at":"2026-05-18T00:12:58Z","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":"Learning inter-domain mappings from unpaired data can improve performance in structured prediction tasks, such as image segmentation, by reducing the need for paired data. CycleGAN was recently proposed for this problem, but critically assumes the underlying inter-domain mapping is approximately deterministic and one-to-one. This assumption renders the model ineffective for tasks requiring flexible, many-to-many mappings. We propose a new model, called Augmented CycleGAN, which learns many-to-many mappings between domains. We examine Augmented CycleGAN qualitatively and quantitatively on sever","authors_text":"Aaron Courville, Alessandro Sordoni, Amjad Almahairi, Philip Bachman, Sai Rajeswar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-27T20:29:20Z","title":"Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10151","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":"sha256:2925aff1905ba9929d17e2b8898ed4010720a885fc9341cfde1519613a8597e2","target":"record","created_at":"2026-05-18T00:12:58Z","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":"99efb8731e890a593daba686bb6a56b826383bfc3a012c4b1bf0da1176baa590","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-27T20:29:20Z","title_canon_sha256":"ac0698e98ec5e56128c9dd0acc41dfd92b83dc8b3558b98528a9fd2ffc1dfe3b"},"schema_version":"1.0","source":{"id":"1802.10151","kind":"arxiv","version":2}},"canonical_sha256":"d2cc9fc935002e6d9837999a4dea9fcac8ff356ee1eac7ed214c76375e35eb3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d2cc9fc935002e6d9837999a4dea9fcac8ff356ee1eac7ed214c76375e35eb3e","first_computed_at":"2026-05-18T00:12:58.479978Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:12:58.479978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9GEHkWNCfWUIJApZpmoZmfYgR5ZeWMPZZnEhUNiFx/6VIrfT4xX0w48O/emsTqn4WtwXAMZymURzDn4bKbu0DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:12:58.480489Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10151","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2925aff1905ba9929d17e2b8898ed4010720a885fc9341cfde1519613a8597e2","sha256:c9026a3778d34b4f7c9f8017b75cec29c26ba95f56ed32e5710211e2b7e79e9e"],"state_sha256":"baf3b5e5e716a2d73c9da14d7557433d7c4f6ebecb743a24d10bbb6d665deaac"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DAK5PRCuB1WUsN8hTRdvGLqJ5qrXY6M7CBHXVI9D9quInRi1MZ+xiJSyuX+0PJYz2+EqCya5v6PPMDJ+FRV2BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T15:35:38.809839Z","bundle_sha256":"4c84559f73090c73fd64ae621c80774232c4c91e526947ca5b7d63537db0739f"}}