{"ID":6497566,"CreatedAt":"2026-07-13T01:19:40.13847098Z","UpdatedAt":"2026-07-14T01:36:59.12045529Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.09655","arxiv_id":"2607.09655","title":"OpenLongTail: Generative Scaling of Long-Tail Driving Data","abstract":"Scaling robust driving policies is fundamentally bottlenecked by the scarcity of edge cases in curated datasets. While the real world continuously captures these critical events, such long-tail events remain underutilized when collected from heterogeneous sources. Specifically, diverse but valuable in-the-wild long-tail videos lack the full view coverage required for training policy models, often missing multi-view poses or originating solely from monocular dash cameras. This modality gap prevents these ubiquitous observations from being converted into scalable training data for long-tail generalization. We introduce OpenLongTail, an open-source generative data engine for scaling autonomous driving policies under long-tail events. To transform heterogeneous data sources into view-aligned and temporally coherent multi-view assets that are useful for policy learning, we develop a pose-informed extrapolative view synthesis pipeline that generates the missing views. We further enhance cross-view consistency and the temporal alignment for the newly generated views by injecting Plücker ray geometry into the scalable generation engine. By synthesizing heterogeneous long-tail data, we observe a significant improvement in closed-loop driving robustness in handling long-tail events. By measuring the extrapolative view synthesis and pose metrics, we validate the effectiveness of OpenLongTail in visual fidelity, cross-view consistency, and ego-trajectory recovery.","short_abstract":"Scaling robust driving policies is fundamentally bottlenecked by the scarcity of edge cases in curated datasets. While the real world continuously captures these critical events, such long-tail events remain underutilized when collected from heterogeneous sources. Specifically, diverse but valuable in-the-wild long-tai...","url_abs":"https://arxiv.org/abs/2607.09655","url_pdf":"https://arxiv.org/pdf/2607.09655v1","authors":"[\"Lulin Liu\",\"Nuo Chen\",\"Yan Wang\",\"Bangya Liu\",\"Wenyan Cong\",\"Hezhen Hu\",\"Boris Ivanovic\",\"Hao Wang\",\"Ziyao Zeng\",\"Xinyu Gong\",\"Yang Zhou\",\"Zixiang Xiong\",\"Dilin Wang\",\"Zhangyang Wang\",\"Weisong Shi\",\"Ruohan Zhang\",\"Marco Pavone\",\"Zhiwen Fan\"]","published":"2026-07-10T17:54:14Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}