{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2MPVFLH7OQBMG7UQIRSUKLCEPE","short_pith_number":"pith:2MPVFLH7","canonical_record":{"source":{"id":"1906.05596","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-13T10:47:56Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"02fdff88089df74f4400c7813920f3c93b11692bd582b3118b2372e833b7f706","abstract_canon_sha256":"2e964576fa1166a407356afc4d4687f9101e0bb28f9828cbc76eb86f864b5058"},"schema_version":"1.0"},"canonical_sha256":"d31f52acff7402c37e904465452c447901c465269a897396c3f7c7c9f9125dc3","source":{"kind":"arxiv","id":"1906.05596","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.05596","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"arxiv_version","alias_value":"1906.05596v1","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.05596","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"pith_short_12","alias_value":"2MPVFLH7OQBM","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2MPVFLH7OQBMG7UQ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2MPVFLH7","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2MPVFLH7OQBMG7UQIRSUKLCEPE","target":"record","payload":{"canonical_record":{"source":{"id":"1906.05596","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-13T10:47:56Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"02fdff88089df74f4400c7813920f3c93b11692bd582b3118b2372e833b7f706","abstract_canon_sha256":"2e964576fa1166a407356afc4d4687f9101e0bb28f9828cbc76eb86f864b5058"},"schema_version":"1.0"},"canonical_sha256":"d31f52acff7402c37e904465452c447901c465269a897396c3f7c7c9f9125dc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:30.223475Z","signature_b64":"BOIR0T3EtSx/XTMMey1bhz4VWZUOOaLnzf7a+KEVZLqo7ksPRjMe1RbEX43mjKM5X3/4KOIPrSEWvAxDJoJ1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d31f52acff7402c37e904465452c447901c465269a897396c3f7c7c9f9125dc3","last_reissued_at":"2026-05-17T23:41:30.222680Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:30.222680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.05596","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":"2026-05-17T23:41:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uXYAXNnz7ulfbYOT4A6edJg34JpapnKNGzYKdZ8cuqT+V7YvLanOUDTzmAiL2eS2qA5PHn/st3L7qMF/60rKBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:58:57.020398Z"},"content_sha256":"687d76ac15a0bc6de2e275c73798b1785775c9ea28fc57fa68e8216998a205e0","schema_version":"1.0","event_id":"sha256:687d76ac15a0bc6de2e275c73798b1785775c9ea28fc57fa68e8216998a205e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2MPVFLH7OQBMG7UQIRSUKLCEPE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"$c^+$GAN: Complementary Fashion Item Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Mithun Das Gupta, Sudhir Kumar","submitted_at":"2019-06-13T10:47:56Z","abstract_excerpt":"We present a conditional generative adversarial model to draw realistic samples from paired fashion clothing distribution and provide real samples to pair with arbitrary fashion units. More concretely, given an image of a shirt, obtained from a fashion magazine, a brochure or even any random click on ones phone, we draw realistic samples from a parameterized conditional distribution learned as a conditional generative adversarial network ($c^+$GAN) to generate the possible pants which can go with the shirt. We start with a classical cGAN model as proposed by Mirza and Osindero [arXiv:1411.1784"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.05596","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":"2026-05-17T23:41:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zhHailJDlahMeq+0TkSF4PzTBbtjc3ILwTqjA3c4gP0cjWFonxmqK1dzzqUGs3LbrdpZpZZ+3bbah+MMkidtCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:58:57.021034Z"},"content_sha256":"2c768bb978cd607c9759f62132fae2cef56d440d5c0ff03883d5a2f31b3abd3e","schema_version":"1.0","event_id":"sha256:2c768bb978cd607c9759f62132fae2cef56d440d5c0ff03883d5a2f31b3abd3e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/bundle.json","state_url":"https://pith.science/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/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":"2026-06-06T19:58:57Z","links":{"resolver":"https://pith.science/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE","bundle":"https://pith.science/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/bundle.json","state":"https://pith.science/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2MPVFLH7OQBMG7UQIRSUKLCEPE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2MPVFLH7OQBMG7UQIRSUKLCEPE","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":"2e964576fa1166a407356afc4d4687f9101e0bb28f9828cbc76eb86f864b5058","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-13T10:47:56Z","title_canon_sha256":"02fdff88089df74f4400c7813920f3c93b11692bd582b3118b2372e833b7f706"},"schema_version":"1.0","source":{"id":"1906.05596","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.05596","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"arxiv_version","alias_value":"1906.05596v1","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.05596","created_at":"2026-05-17T23:41:30Z"},{"alias_kind":"pith_short_12","alias_value":"2MPVFLH7OQBM","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2MPVFLH7OQBMG7UQ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2MPVFLH7","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:2c768bb978cd607c9759f62132fae2cef56d440d5c0ff03883d5a2f31b3abd3e","target":"graph","created_at":"2026-05-17T23:41:30Z","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":"We present a conditional generative adversarial model to draw realistic samples from paired fashion clothing distribution and provide real samples to pair with arbitrary fashion units. More concretely, given an image of a shirt, obtained from a fashion magazine, a brochure or even any random click on ones phone, we draw realistic samples from a parameterized conditional distribution learned as a conditional generative adversarial network ($c^+$GAN) to generate the possible pants which can go with the shirt. We start with a classical cGAN model as proposed by Mirza and Osindero [arXiv:1411.1784","authors_text":"Mithun Das Gupta, Sudhir Kumar","cross_cats":["cs.IR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-13T10:47:56Z","title":"$c^+$GAN: Complementary Fashion Item Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.05596","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":"sha256:687d76ac15a0bc6de2e275c73798b1785775c9ea28fc57fa68e8216998a205e0","target":"record","created_at":"2026-05-17T23:41:30Z","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":"2e964576fa1166a407356afc4d4687f9101e0bb28f9828cbc76eb86f864b5058","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-13T10:47:56Z","title_canon_sha256":"02fdff88089df74f4400c7813920f3c93b11692bd582b3118b2372e833b7f706"},"schema_version":"1.0","source":{"id":"1906.05596","kind":"arxiv","version":1}},"canonical_sha256":"d31f52acff7402c37e904465452c447901c465269a897396c3f7c7c9f9125dc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d31f52acff7402c37e904465452c447901c465269a897396c3f7c7c9f9125dc3","first_computed_at":"2026-05-17T23:41:30.222680Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:30.222680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BOIR0T3EtSx/XTMMey1bhz4VWZUOOaLnzf7a+KEVZLqo7ksPRjMe1RbEX43mjKM5X3/4KOIPrSEWvAxDJoJ1Bw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:30.223475Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.05596","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:687d76ac15a0bc6de2e275c73798b1785775c9ea28fc57fa68e8216998a205e0","sha256:2c768bb978cd607c9759f62132fae2cef56d440d5c0ff03883d5a2f31b3abd3e"],"state_sha256":"41ff30c33aabe88b7cffb5f5c9b346c4e747dd324395dc2be51ec028bde56cfa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ID14eog7/aVozrfF0NpI3LHXxnQXRmLxyA7aB/luuuLWh5aq3x3K//pnUYfRpjtuIHYsXl+VeJ/+R/wyOYUNDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T19:58:57.024501Z","bundle_sha256":"7a80300c798d9e372b4072d48ed26f9c1be1456f9506d40fa1389aa4f8e90bda"}}