The paper fine-tunes Qwen3.5-4B as a driving VLA using serialized decision traces from rule-based planners, reporting reduced ADE and miss rate on a simulator benchmark with camera inputs.
More than meets the eye? uncovering the reasoning-planning disconnect in training vision-language driving models.arXiv preprint arXiv:2510.04532, 2025
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Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAs
The paper fine-tunes Qwen3.5-4B as a driving VLA using serialized decision traces from rule-based planners, reporting reduced ADE and miss rate on a simulator benchmark with camera inputs.