**FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Plannin

**FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planning**

> Multimodal driving planning faces a long-standing tension between two paradigms: scoring-based methods benefit from dense reward supervision but are confined to a fixed action vocabulary, while anchor-based methods generate proposals dynamically yet suffer from sparse supervision constrained to a single ground-truth trajectory. In this work, we propose FlowR2A, which resolves this tension by reframing simulation-base...

**来源信息**
- **来源**：HuggingFace Daily Papers（社区热门论文）
- **分类**：ai-models
- **发布时间**：2026-06-24 08:00（北京时间）
- **原文**：[打开原文](https://huggingface.co/papers/2606.24231)