Navigating User Behavior toward Personalized Multimodal Generation

Computer Science > Artificial Intelligence [Submitted on 23 Jun 2026] Navigating User Behavior toward Personalized Multimodal Generation Hengji Zhou, Yufeng Liu, Ye Liu, Yong Xu, Lianghao Xia, Liqiang Nie Modern AIGC pipelines deliver high-fidelity images and videos but presuppose a well-formed creation instruction, while end users rarely articulate visual details, leaving generators misaligned with user demand. We study personalized content generation, which turns a user's interaction history into an executable instruction for downstream synthesis, and identify two obstacles: behavior must be encoded in a form legible to language reasoning, and the model must acquire instruction-writing skill absent from both pretraining and behavior data. We propose NaviGen, which represents each item with a dual identifier coupling a collaborative code and a textual code as a behavioral substrate and a semantic bridge in one token stream. On this representation, a two-stage SFT+RL pipeline first distills preference reasoning and instruction writing from evolutionarily searched supervision, then aligns generation with user intent through hierarchical and self-consistent rewards. Experiments across product, game, and short-video domains show that NaviGen improves personalized image and video generation, strengthens next-item prediction, and yields more specific, relevant, and visually generatable instructions. Our code is anonymously released at: this https URL. Comments: 16 pages, 15 figures, 5 tables. Code is available at this https URL Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2606.24196 [cs.AI]   (or arXiv:2606.24196v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.24196 Focus to learn more Submission history From: Hengji Zhou [view email] [v1] Tue, 23 Jun 2026 06:31:21 UTC (3,769 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)