{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:323Y7I6CQXIV7TNIGSYFVPTVB3","short_pith_number":"pith:323Y7I6C","canonical_record":{"source":{"id":"2506.03652","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-04T07:43:51Z","cross_cats_sorted":[],"title_canon_sha256":"bbbd9004782d54bf64327093d0b979ca87d4cbf22fefe9819daf79c25171bcad","abstract_canon_sha256":"a44e87e8ebe51955c7c0cd2cbc03af1a43e6e4c73d148b1278e7ac4687fc27e4"},"schema_version":"1.0"},"canonical_sha256":"deb78fa3c285d15fcda834b05abe750ec8939cdb459695712cceb2ff2586121c","source":{"kind":"arxiv","id":"2506.03652","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03652","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03652v1","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03652","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"323Y7I6CQXIV","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_16","alias_value":"323Y7I6CQXIV7TNI","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_8","alias_value":"323Y7I6C","created_at":"2026-07-05T11:15:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:323Y7I6CQXIV7TNIGSYFVPTVB3","target":"record","payload":{"canonical_record":{"source":{"id":"2506.03652","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-04T07:43:51Z","cross_cats_sorted":[],"title_canon_sha256":"bbbd9004782d54bf64327093d0b979ca87d4cbf22fefe9819daf79c25171bcad","abstract_canon_sha256":"a44e87e8ebe51955c7c0cd2cbc03af1a43e6e4c73d148b1278e7ac4687fc27e4"},"schema_version":"1.0"},"canonical_sha256":"deb78fa3c285d15fcda834b05abe750ec8939cdb459695712cceb2ff2586121c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:15:49.426557Z","signature_b64":"e23RqlEVqx4eEvJJxnS+splmr3ang2ZbbLf3/UzHfbQk/+IeYmBDH8gme5BZdchDHVd32MbEDnytzriFv4dLBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"deb78fa3c285d15fcda834b05abe750ec8939cdb459695712cceb2ff2586121c","last_reissued_at":"2026-07-05T11:15:49.425998Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:15:49.425998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.03652","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":"2026-07-05T11:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d8X9AwPXQSgg5rooA+zGyMZXY1BPC+0xoZbQjOsHwsg4xg7V3Hb3Md72v8XTTHKmE4Gi0N35/JVyuqn3ORw2Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:40:46.224869Z"},"content_sha256":"82c480e089d3cda324b3d03fe5675f12f24e98f2ddebf0aa5b1486adefced359","schema_version":"1.0","event_id":"sha256:82c480e089d3cda324b3d03fe5675f12f24e98f2ddebf0aa5b1486adefced359"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:323Y7I6CQXIV7TNIGSYFVPTVB3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EmoArt: A Multidimensional Dataset for Emotion-Aware Artistic Generation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bin Wen, Cheng Zhang, Hongxia Xie, Ruoxuan Zhang, Songhan Zuo, Wen-Huang Cheng","submitted_at":"2025-06-04T07:43:51Z","abstract_excerpt":"With the rapid advancement of diffusion models, text-to-image generation has achieved significant progress in image resolution, detail fidelity, and semantic alignment, particularly with models like Stable Diffusion 3.5, Stable Diffusion XL, and FLUX 1. However, generating emotionally expressive and abstract artistic images remains a major challenge, largely due to the lack of large-scale, fine-grained emotional datasets. To address this gap, we present the EmoArt Dataset -- one of the most comprehensive emotion-annotated art datasets to date. It contains 132,664 artworks across 56 painting st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03652","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/2506.03652/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":"2026-07-05T11:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iQZ75xMkbFNEcjZONWmJ7zoD0xtUnDwDF4N7KeAjfZixSmo7XRlvMDFJoVoHXRzp89Z5cGuMS8fj/GmA/OacAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:40:46.225377Z"},"content_sha256":"8267286ab0e5fd7338f0be8b1358c981ff4f9e3fc187e1c604ea4dcc1eb6c146","schema_version":"1.0","event_id":"sha256:8267286ab0e5fd7338f0be8b1358c981ff4f9e3fc187e1c604ea4dcc1eb6c146"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/bundle.json","state_url":"https://pith.science/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/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":"2026-08-09T01:40:46Z","links":{"resolver":"https://pith.science/pith/323Y7I6CQXIV7TNIGSYFVPTVB3","bundle":"https://pith.science/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/bundle.json","state":"https://pith.science/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/323Y7I6CQXIV7TNIGSYFVPTVB3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:323Y7I6CQXIV7TNIGSYFVPTVB3","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":"a44e87e8ebe51955c7c0cd2cbc03af1a43e6e4c73d148b1278e7ac4687fc27e4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-04T07:43:51Z","title_canon_sha256":"bbbd9004782d54bf64327093d0b979ca87d4cbf22fefe9819daf79c25171bcad"},"schema_version":"1.0","source":{"id":"2506.03652","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03652","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03652v1","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03652","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"323Y7I6CQXIV","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_16","alias_value":"323Y7I6CQXIV7TNI","created_at":"2026-07-05T11:15:49Z"},{"alias_kind":"pith_short_8","alias_value":"323Y7I6C","created_at":"2026-07-05T11:15:49Z"}],"graph_snapshots":[{"event_id":"sha256:8267286ab0e5fd7338f0be8b1358c981ff4f9e3fc187e1c604ea4dcc1eb6c146","target":"graph","created_at":"2026-07-05T11:15:49Z","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/2506.03652/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid advancement of diffusion models, text-to-image generation has achieved significant progress in image resolution, detail fidelity, and semantic alignment, particularly with models like Stable Diffusion 3.5, Stable Diffusion XL, and FLUX 1. However, generating emotionally expressive and abstract artistic images remains a major challenge, largely due to the lack of large-scale, fine-grained emotional datasets. To address this gap, we present the EmoArt Dataset -- one of the most comprehensive emotion-annotated art datasets to date. It contains 132,664 artworks across 56 painting st","authors_text":"Bin Wen, Cheng Zhang, Hongxia Xie, Ruoxuan Zhang, Songhan Zuo, Wen-Huang Cheng","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-04T07:43:51Z","title":"EmoArt: A Multidimensional Dataset for Emotion-Aware Artistic Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03652","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":"sha256:82c480e089d3cda324b3d03fe5675f12f24e98f2ddebf0aa5b1486adefced359","target":"record","created_at":"2026-07-05T11:15:49Z","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":"a44e87e8ebe51955c7c0cd2cbc03af1a43e6e4c73d148b1278e7ac4687fc27e4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-04T07:43:51Z","title_canon_sha256":"bbbd9004782d54bf64327093d0b979ca87d4cbf22fefe9819daf79c25171bcad"},"schema_version":"1.0","source":{"id":"2506.03652","kind":"arxiv","version":1}},"canonical_sha256":"deb78fa3c285d15fcda834b05abe750ec8939cdb459695712cceb2ff2586121c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"deb78fa3c285d15fcda834b05abe750ec8939cdb459695712cceb2ff2586121c","first_computed_at":"2026-07-05T11:15:49.425998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:15:49.425998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e23RqlEVqx4eEvJJxnS+splmr3ang2ZbbLf3/UzHfbQk/+IeYmBDH8gme5BZdchDHVd32MbEDnytzriFv4dLBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:15:49.426557Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03652","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82c480e089d3cda324b3d03fe5675f12f24e98f2ddebf0aa5b1486adefced359","sha256:8267286ab0e5fd7338f0be8b1358c981ff4f9e3fc187e1c604ea4dcc1eb6c146"],"state_sha256":"017584503449e8553a6dd403c2ac0b3abd502c040a8353b348e21e8abe98fa89"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"raOI1VRhwCcDpnueL9qm/IGFeHaiBdJ4L40vreuSuAjnWz9ctXN9vs7eqPJlGN9wmacb82kRccAifa56GzHXCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T01:40:46.229041Z","bundle_sha256":"ba330d7ddb6aedd6ef11b822fd3714c7a588ea8c186570e2e507b3e753160377"}}