FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory

arXiv:2609.18623 · cs.CV, cs.RO · Submitted 2026-09-16 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-16

Updated: 2026-09-16

Code: https://github.com/OpenDriveLab/DriveLM

Terminology

Fine-Tuning — 26× in this paper · explained in 5 episodes
Benchmark — 16× in this paper · explained in 2 episodes
Robustness — 12× in this paper · explained in 5 episodes
Recurrent Action Memory — 10× in this paper
Transformer — 9× in this paper · explained in 2 episodes
Edge Devices — 7× in this paper · explained in 2 episodes
International Conference on Learning Representations — 7× in this paper
Steering — 7× in this paper · explained in 2 episodes
Accuracy — 6× in this paper · explained in 1 episode
International Conference on Computer Vision — 6× in this paper
Ablation — 5× in this paper · explained in 1 episode
Conference on Computer Vision and Pattern Recognition — 5× in this paper
Adaptation — 4× in this paper · explained in 1 episode
Driving Score — 4× in this paper
Benchmarking — 3× in this paper · explained in 3 episodes
Foundation Model — 3× in this paper · explained in 3 episodes
Foundation Models — 3× in this paper · explained in 7 episodes
PID Controller — 3× in this paper · explained in 2 episodes
Temporal Reasoning — 3× in this paper · explained in 2 episodes
Tiny Recursive Model — 3× in this paper
Transfer Learning — 3× in this paper · explained in 10 episodes
Action Decoder — 2× in this paper · explained in 1 episode
European Conference on Computer Vision — 2× in this paper
Explainability — 2× in this paper · explained in 3 episodes
Generalization — 2× in this paper · explained in 13 episodes
In International Conference on Machine Learning — 2× in this paper
Parameter-Efficient Fine-Tuning — 2× in this paper · explained in 2 episodes
Action Space — 1× in this paper · explained in 1 episode
Adam — 1× in this paper · explained in 2 episodes
Adaptive Lookahead — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Alignment — 1× in this paper · explained in 1 episode
Attention Mechanism — 1× in this paper · explained in 3 episodes
Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
Chain-of-Thought (CoT) Reasoning — 1× in this paper · explained in 2 episodes
Commentary — 1× in this paper · explained in 2 episodes
Covariate Shift — 1× in this paper · explained in 2 episodes
Domain Shift — 1× in this paper · explained in 4 episodes
Few-Shot Learning — 1× in this paper · explained in 4 episodes
Foundation Models (FMs) — 1× in this paper · explained in 2 episodes
Gradient Flow — 1× in this paper · explained in 2 episodes
Instruction Tuning — 1× in this paper · explained in 2 episodes
LLM judge — 1× in this paper · explained in 2 episodes
Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
Reinforcement Learning — 1× in this paper · explained in 4 episodes
Representation Learning — 1× in this paper · explained in 2 episodes
Semantic Understanding — 1× in this paper · explained in 2 episodes
Transactions on Machine Learning Research — 1× in this paper
Two-stage training — 1× in this paper · explained in 2 episodes
World Model — 1× in this paper · explained in 7 episodes

FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory

Terminology

Sources

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