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ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing

ForcingDAS is introduced, a unified and robust DA framework that learns a joint-trajectory prior instead of frame-to-frame transitions that allows it to capture long-horizon temporal dependencies and reduce error accumulation.

Yi-Xuan Jia, Si-Yi Chen, Yi Pan et al. · 3 citations
Oct 2026

MUSE: Target-Guided Multimodal Scoring Ensemble for Safe Autonomous Planning

Imitation learning planners can behave unsafely under distribution shift, since long-tailed driving data contain few safety-critical events. A common remedy is to generate multimodal candidate trajectories and select them with a hybrid evaluator, but existing methods often suffer from mode collapse and brittle hard con...

Wenxiao Ke, Wen-Jie Lu, Fu-Jun Peng et al. · 0 citations

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