{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UXCAAY5VVLGGVSPOR3QQRKRZJA","short_pith_number":"pith:UXCAAY5V","schema_version":"1.0","canonical_sha256":"a5c40063b5aacc6ac9ee8ee108aa394833838ce215e23aa91bf5406f082c3703","source":{"kind":"arxiv","id":"2503.10112","version":1},"attestation_state":"computed","paper":{"title":"MoEdit: On Learning Quantity Perception for Multi-object Image Editing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"ChanTong Lam, Kahou Chan, Keren Fu, Tao Tan, Tong Tong, Xiaohong Liu, Yanfeng Li, Yue Sun, Zitong Yu","submitted_at":"2025-03-13T07:13:54Z","abstract_excerpt":"Multi-object images are prevalent in various real-world scenarios, including augmented reality, advertisement design, and medical imaging. Efficient and precise editing of these images is critical for these applications. With the advent of Stable Diffusion (SD), high-quality image generation and editing have entered a new era. However, existing methods often struggle to consider each object both individually and part of the whole image editing, both of which are crucial for ensuring consistent quantity perception, resulting in suboptimal perceptual performance. To address these challenges, we "},"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":"2503.10112","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T07:13:54Z","cross_cats_sorted":[],"title_canon_sha256":"e5752225ae0e0d4ea6b36165d091db374f1e2df294d6bac07ea2ad9213b60ada","abstract_canon_sha256":"b3f334719ed0bde7f3ac4dff28c977a204abbd032d03134680a3ff8cb0cf667c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:30:38.689047Z","signature_b64":"LxAZnDyKLJEKcqpm++6iu/FCDIwDTRP3rrrc5QN1plc2H/E6hzIw7u/orFD57Ec7pVWmGcExdFsNFZj3oIDfBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a5c40063b5aacc6ac9ee8ee108aa394833838ce215e23aa91bf5406f082c3703","last_reissued_at":"2026-07-05T10:30:38.688390Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:30:38.688390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MoEdit: On Learning Quantity Perception for Multi-object Image Editing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"ChanTong Lam, Kahou Chan, Keren Fu, Tao Tan, Tong Tong, Xiaohong Liu, Yanfeng Li, Yue Sun, Zitong Yu","submitted_at":"2025-03-13T07:13:54Z","abstract_excerpt":"Multi-object images are prevalent in various real-world scenarios, including augmented reality, advertisement design, and medical imaging. Efficient and precise editing of these images is critical for these applications. With the advent of Stable Diffusion (SD), high-quality image generation and editing have entered a new era. However, existing methods often struggle to consider each object both individually and part of the whole image editing, both of which are crucial for ensuring consistent quantity perception, resulting in suboptimal perceptual performance. To address these challenges, we "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.10112","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/2503.10112/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":"2503.10112","created_at":"2026-07-05T10:30:38.688481+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.10112v1","created_at":"2026-07-05T10:30:38.688481+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.10112","created_at":"2026-07-05T10:30:38.688481+00:00"},{"alias_kind":"pith_short_12","alias_value":"UXCAAY5VVLGG","created_at":"2026-07-05T10:30:38.688481+00:00"},{"alias_kind":"pith_short_16","alias_value":"UXCAAY5VVLGGVSPO","created_at":"2026-07-05T10:30:38.688481+00:00"},{"alias_kind":"pith_short_8","alias_value":"UXCAAY5V","created_at":"2026-07-05T10:30:38.688481+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/UXCAAY5VVLGGVSPOR3QQRKRZJA","json":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA.json","graph_json":"https://pith.science/api/pith-number/UXCAAY5VVLGGVSPOR3QQRKRZJA/graph.json","events_json":"https://pith.science/api/pith-number/UXCAAY5VVLGGVSPOR3QQRKRZJA/events.json","paper":"https://pith.science/paper/UXCAAY5V"},"agent_actions":{"view_html":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA","download_json":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA.json","view_paper":"https://pith.science/paper/UXCAAY5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.10112&json=true","fetch_graph":"https://pith.science/api/pith-number/UXCAAY5VVLGGVSPOR3QQRKRZJA/graph.json","fetch_events":"https://pith.science/api/pith-number/UXCAAY5VVLGGVSPOR3QQRKRZJA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA/action/storage_attestation","attest_author":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA/action/author_attestation","sign_citation":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA/action/citation_signature","submit_replication":"https://pith.science/pith/UXCAAY5VVLGGVSPOR3QQRKRZJA/action/replication_record"}},"created_at":"2026-07-05T10:30:38.688481+00:00","updated_at":"2026-07-05T10:30:38.688481+00:00"}