FleetAgent pairs a vector-to-embedding interface (VecFormer) with an MLLM to turn compact V2N messages into structured natural-language teleoperation assistance, cutting uplink payload 625x and improving Lingo-Judge score 16.8% on a new nuScenes-derived dataset.
ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
VLADriveBench combines observational metrics and CoT intervention protocols to evaluate the relevance and causality of reasoning in vision-language-action models for autonomous driving, revealing divergent model behaviors.
citing papers explorer
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FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages
FleetAgent pairs a vector-to-embedding interface (VecFormer) with an MLLM to turn compact V2N messages into structured natural-language teleoperation assistance, cutting uplink payload 625x and improving Lingo-Judge score 16.8% on a new nuScenes-derived dataset.
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VLADriveBench: Evaluating CoT-Action Relationship in VLA for Autonomous Driving
VLADriveBench combines observational metrics and CoT intervention protocols to evaluate the relevance and causality of reasoning in vision-language-action models for autonomous driving, revealing divergent model behaviors.