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Due to the scarcity of style\u2010specific data, existing approaches pull the generative prior towards a reference style, which often results in out\u2010of\u2010distribution, low\u2010quality generations. In this work, we introduce LoRA\u2010MDM, a lightweight framework for motion stylization that generalizes to complex actions while maintaining editability. Our key insight is that adapting the generative prior to include the style, while preserving its overall distribution, is more effective than modifying each individual motion during generation. Building on this idea, LoRA\u2010MDM learns to adapt the prior to include the reference style using only a few samples. The style can then be used in the context of different textual prompts for generation. The low\u2010rank adaptation shifts the motion manifold in a semantically meaningful way, enabling realistic style infusion even for actions not present in the reference samples. Moreover, preserving the distribution structure enables advanced operations such as style blending and motion editing. We compare LoRA\u2010MDM to state\u2010of\u2010the\u2010art stylized motion generation methods and demonstrate a favorable balance between text fidelity and style consistency. Project page at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/haimsaw.github.io\/LoRA-MDM\/\">https:\/\/haimsaw.github.io\/LoRA\u2010MDM\/<\/jats:ext-link>\n                  <\/jats:p>","DOI":"10.1111\/cgf.70365","type":"journal-article","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T12:44:50Z","timestamp":1774874690000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Dance Like a Chicken: Low\u2010Rank Stylization for Human Motion Diffusion"],"prefix":"10.1111","author":[{"given":"Haim","family":"Sawdayee","sequence":"first","affiliation":[{"name":"The Blavatnik School of Computer Science Tel Aviv University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuan","family":"Guo","sequence":"additional","affiliation":[{"name":"Snap Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guy","family":"Tevet","sequence":"additional","affiliation":[{"name":"The Blavatnik School of Computer Science Tel Aviv University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Snap Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Snap Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit H.","family":"Bermano","sequence":"additional","affiliation":[{"name":"The Blavatnik School of Computer Science Tel Aviv University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,30]]},"reference":[{"issue":"4","key":"e_1_2_8_2_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3592458","article-title":"Listen, denoise, action! audio-driven motion synthesis with diffusion models","volume":"42","author":"Alexanderson S.","year":"2023","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"e_1_2_8_3_2","doi-asserted-by":"crossref","unstructured":"ArarM. 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