Quantile Head for Vision-Language-Action Models

arXiv:2609.34061 · cs.RO, cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.RO, cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/xwangrs/Quantile-Head-for-VLA

Terminology

• Flow Matching — 30× in this paper · explained in 8 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Generalization — 6× in this paper · explained in 13 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Zero-Shot Transfer — 3× in this paper · explained in 4 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Self-Distillation — 2× in this paper · explained in 7 episodes
• VLA Models — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Action Flow — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Compositional Generalization — 1× in this paper · explained in 4 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control
• Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models
• Geometric Action Model for Robot Policy Learning
• SUREFlow: State-space Uncertainty-aware REsidual Flow Matching for Robust Robot Manipulation
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• MolmoAct: Action Reasoning Models that can Reason in Space
• SnapFlow: One-Step Action Generation for Flow-Matching VLAs via Progressive Self-Distillation
• SimVLA: A Simple VLA Baseline for Robotic Manipulation
• InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization
• FAST: Efficient Action Tokenization for Vision-Language-Action Models
• Learning Policies through Quantile Regression
• MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models
• VLANeXt Family: A Systematic Study of VLA Models from Core Recipes to Emerging Paradigms
• Continuous Reasoning for Vision-Language-Action
• World-Language-Action Model for Unified World Modeling, Language Reasoning, and Action Synthesis
• CofactVLA: Deconfounding Vision-Language-Action Models via Counterfactual Intervention
• LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

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