{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:2AN5HNTZ7YLGZ7FK5ELPML7PKA","short_pith_number":"pith:2AN5HNTZ","schema_version":"1.0","canonical_sha256":"d01bd3b679fe166cfcaae916f62fef5039c6aa986434db1683402284975dd4e0","source":{"kind":"arxiv","id":"2507.10217","version":2},"attestation_state":"computed","paper":{"title":"From Wardrobe to Canvas: Wardrobe Polyptych LoRA for Part-level Controllable Human Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hyoungwoo Park, Jaegul Choo, Jeongho Kim, Seokeon Choi, Sunghyun Park, Sungrack Yun","submitted_at":"2025-07-14T12:34:25Z","abstract_excerpt":"Recent diffusion models achieve personalization by learning specific subjects, allowing learned attributes to be integrated into generated images. However, personalized human image generation remains challenging due to the need for precise and consistent attribute preservation (e.g., identity, clothing details). Existing subject-driven image generation methods often require either (1) inference-time fine-tuning with few images for each new subject or (2) large-scale dataset training for generalization. Both approaches are computationally expensive and impractical for real-time applications. To"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.10217","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-14T12:34:25Z","cross_cats_sorted":[],"title_canon_sha256":"e79daae259c27b217de3a9193e52df12353029ee25d17dc7564a052f6a67f488","abstract_canon_sha256":"467b5147ebf7842966eb7e6bee62f37cf75bb16577cf721e35fb4c50b5074159"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:40:01.201362Z","signature_b64":"a5i2ueMq6bD87FEoS8E01KWZ8Yfb+Fk2i2h2Slldm+PwWHMBuzqsN7XKtY0Fochpio83R+r1YOhpfGZBSdIiAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d01bd3b679fe166cfcaae916f62fef5039c6aa986434db1683402284975dd4e0","last_reissued_at":"2026-07-05T11:40:01.200868Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:40:01.200868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"From Wardrobe to Canvas: Wardrobe Polyptych LoRA for Part-level Controllable Human Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hyoungwoo Park, Jaegul Choo, Jeongho Kim, Seokeon Choi, Sunghyun Park, Sungrack Yun","submitted_at":"2025-07-14T12:34:25Z","abstract_excerpt":"Recent diffusion models achieve personalization by learning specific subjects, allowing learned attributes to be integrated into generated images. However, personalized human image generation remains challenging due to the need for precise and consistent attribute preservation (e.g., identity, clothing details). Existing subject-driven image generation methods often require either (1) inference-time fine-tuning with few images for each new subject or (2) large-scale dataset training for generalization. Both approaches are computationally expensive and impractical for real-time applications. To"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.10217","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.10217/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.10217","created_at":"2026-07-05T11:40:01.200934+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.10217v2","created_at":"2026-07-05T11:40:01.200934+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.10217","created_at":"2026-07-05T11:40:01.200934+00:00"},{"alias_kind":"pith_short_12","alias_value":"2AN5HNTZ7YLG","created_at":"2026-07-05T11:40:01.200934+00:00"},{"alias_kind":"pith_short_16","alias_value":"2AN5HNTZ7YLGZ7FK","created_at":"2026-07-05T11:40:01.200934+00:00"},{"alias_kind":"pith_short_8","alias_value":"2AN5HNTZ","created_at":"2026-07-05T11:40:01.200934+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA","json":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA.json","graph_json":"https://pith.science/api/pith-number/2AN5HNTZ7YLGZ7FK5ELPML7PKA/graph.json","events_json":"https://pith.science/api/pith-number/2AN5HNTZ7YLGZ7FK5ELPML7PKA/events.json","paper":"https://pith.science/paper/2AN5HNTZ"},"agent_actions":{"view_html":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA","download_json":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA.json","view_paper":"https://pith.science/paper/2AN5HNTZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.10217&json=true","fetch_graph":"https://pith.science/api/pith-number/2AN5HNTZ7YLGZ7FK5ELPML7PKA/graph.json","fetch_events":"https://pith.science/api/pith-number/2AN5HNTZ7YLGZ7FK5ELPML7PKA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA/action/storage_attestation","attest_author":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA/action/author_attestation","sign_citation":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA/action/citation_signature","submit_replication":"https://pith.science/pith/2AN5HNTZ7YLGZ7FK5ELPML7PKA/action/replication_record"}},"created_at":"2026-07-05T11:40:01.200934+00:00","updated_at":"2026-07-05T11:40:01.200934+00:00"}