{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W6UIF5HQQ4ZCIOD6J24TA7G36E","short_pith_number":"pith:W6UIF5HQ","canonical_record":{"source":{"id":"2412.03957","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T08:15:37Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"88b387de44fe93d3d14d0983bcbbb516ac40439016b5ca2f9cd2fc93a7ff3aaa","abstract_canon_sha256":"e4bbf5ffcafe4cd7c1025798a6612ad70579f6704b9bc2b215bcb900e7b343d4"},"schema_version":"1.0"},"canonical_sha256":"b7a882f4f0873224387e4eb9307cdbf10806fabc63722389a387bab5949b7a77","source":{"kind":"arxiv","id":"2412.03957","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03957","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03957v1","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03957","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_12","alias_value":"W6UIF5HQQ4ZC","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_16","alias_value":"W6UIF5HQQ4ZCIOD6","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_8","alias_value":"W6UIF5HQ","created_at":"2026-07-05T09:44:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W6UIF5HQQ4ZCIOD6J24TA7G36E","target":"record","payload":{"canonical_record":{"source":{"id":"2412.03957","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T08:15:37Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"88b387de44fe93d3d14d0983bcbbb516ac40439016b5ca2f9cd2fc93a7ff3aaa","abstract_canon_sha256":"e4bbf5ffcafe4cd7c1025798a6612ad70579f6704b9bc2b215bcb900e7b343d4"},"schema_version":"1.0"},"canonical_sha256":"b7a882f4f0873224387e4eb9307cdbf10806fabc63722389a387bab5949b7a77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:44:57.049672Z","signature_b64":"Je75svWTCp5k9NY8QoNVvMeNpORWD6IbXa6jpLQF4u9Lmi1lMBq0KEYQzwtzDQNh8P2Nx3yjypgK8WsramA3BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7a882f4f0873224387e4eb9307cdbf10806fabc63722389a387bab5949b7a77","last_reissued_at":"2026-07-05T09:44:57.048982Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:44:57.048982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.03957","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":"2026-07-05T09:44:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c9QrciwAADHe7j7AThLaNZZ1hkl/rCx4j4wiFgvoP5EPpKBLmSpYvc1SG7aCp2NFUjoJp9UhFLWCotp0f+/2Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:31:29.137488Z"},"content_sha256":"fd3c34dc8aafe5e03d945ac6d7f41a9d6470108f8db34762c9d1ee0e123b1ea0","schema_version":"1.0","event_id":"sha256:fd3c34dc8aafe5e03d945ac6d7f41a9d6470108f8db34762c9d1ee0e123b1ea0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W6UIF5HQQ4ZCIOD6J24TA7G36E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Framework For Image Synthesis Using Supervised Contrastive Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Gang Pan, Jianyu Zhang, Li Zhang, Shijian Li, Yibin Liu","submitted_at":"2024-12-05T08:15:37Z","abstract_excerpt":"Text-to-image (T2I) generation aims at producing realistic images corresponding to text descriptions. Generative Adversarial Network (GAN) has proven to be successful in this task. Typical T2I GANs are 2 phase methods that first pretrain an inter-modal representation from aligned image-text pairs and then use GAN to train image generator on that basis. However, such representation ignores the inner-modal semantic correspondence, e.g. the images with same label. The semantic label in priory describes the inherent distribution pattern with underlying cross-image relationships, which is supplemen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03957","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.03957/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T09:44:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YtliGb1LHQ6TBSIGNtZ/8o3i0onLIxYPNaPSi23rzRpuBtiXqqgWTqp+5tCIIVbMUzq+tl1OQqLWR4jf/mfKAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:31:29.138067Z"},"content_sha256":"6a82804182b9157d7ecddb5e70d256ed331f9fce54f7a8f02a9379ae055f1f0d","schema_version":"1.0","event_id":"sha256:6a82804182b9157d7ecddb5e70d256ed331f9fce54f7a8f02a9379ae055f1f0d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/bundle.json","state_url":"https://pith.science/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/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":"2026-08-18T23:31:29Z","links":{"resolver":"https://pith.science/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E","bundle":"https://pith.science/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/bundle.json","state":"https://pith.science/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W6UIF5HQQ4ZCIOD6J24TA7G36E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W6UIF5HQQ4ZCIOD6J24TA7G36E","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":"e4bbf5ffcafe4cd7c1025798a6612ad70579f6704b9bc2b215bcb900e7b343d4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T08:15:37Z","title_canon_sha256":"88b387de44fe93d3d14d0983bcbbb516ac40439016b5ca2f9cd2fc93a7ff3aaa"},"schema_version":"1.0","source":{"id":"2412.03957","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03957","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03957v1","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03957","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_12","alias_value":"W6UIF5HQQ4ZC","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_16","alias_value":"W6UIF5HQQ4ZCIOD6","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_8","alias_value":"W6UIF5HQ","created_at":"2026-07-05T09:44:57Z"}],"graph_snapshots":[{"event_id":"sha256:6a82804182b9157d7ecddb5e70d256ed331f9fce54f7a8f02a9379ae055f1f0d","target":"graph","created_at":"2026-07-05T09:44:57Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.03957/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-to-image (T2I) generation aims at producing realistic images corresponding to text descriptions. Generative Adversarial Network (GAN) has proven to be successful in this task. Typical T2I GANs are 2 phase methods that first pretrain an inter-modal representation from aligned image-text pairs and then use GAN to train image generator on that basis. However, such representation ignores the inner-modal semantic correspondence, e.g. the images with same label. The semantic label in priory describes the inherent distribution pattern with underlying cross-image relationships, which is supplemen","authors_text":"Gang Pan, Jianyu Zhang, Li Zhang, Shijian Li, Yibin Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T08:15:37Z","title":"A Framework For Image Synthesis Using Supervised Contrastive Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03957","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:fd3c34dc8aafe5e03d945ac6d7f41a9d6470108f8db34762c9d1ee0e123b1ea0","target":"record","created_at":"2026-07-05T09:44:57Z","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":"e4bbf5ffcafe4cd7c1025798a6612ad70579f6704b9bc2b215bcb900e7b343d4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T08:15:37Z","title_canon_sha256":"88b387de44fe93d3d14d0983bcbbb516ac40439016b5ca2f9cd2fc93a7ff3aaa"},"schema_version":"1.0","source":{"id":"2412.03957","kind":"arxiv","version":1}},"canonical_sha256":"b7a882f4f0873224387e4eb9307cdbf10806fabc63722389a387bab5949b7a77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7a882f4f0873224387e4eb9307cdbf10806fabc63722389a387bab5949b7a77","first_computed_at":"2026-07-05T09:44:57.048982Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:44:57.048982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Je75svWTCp5k9NY8QoNVvMeNpORWD6IbXa6jpLQF4u9Lmi1lMBq0KEYQzwtzDQNh8P2Nx3yjypgK8WsramA3BA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:44:57.049672Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.03957","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd3c34dc8aafe5e03d945ac6d7f41a9d6470108f8db34762c9d1ee0e123b1ea0","sha256:6a82804182b9157d7ecddb5e70d256ed331f9fce54f7a8f02a9379ae055f1f0d"],"state_sha256":"aa1a98143cda66f4e713ad4bf7f6776180724bf880a336f55d9b64dd47039d28"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sBH4QtHy6Vj80anohA0nBVn/ugYg9zKC+vA9GXyQ2Xi4yFKZbhqBRNq44JqvTCXG/J3C91+iU5WRS1SiwCiUAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T23:31:29.154479Z","bundle_sha256":"d80c740aa17f4e322da7f7f0b51f178a31da04aef55824e4b79625b9dcf12653"}}