SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models
cs.RO, cs.AI, cs.LG
Submitted: 2026-02-04
Updated: 2026-08-28
Code: https://github.com/snumprlab/scale
Terminology
Sources
- Deep Think with Confidence
- Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
- Verifier-free Test-Time Sampling for Vision-Language-Action Models
- ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver
- Evaluating Uncertainty and Quality of Visual Language Action-enabled Robots
- Policy Contrastive Decoding for Robotic Foundation Models
- AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention
- Steering Vision-Language-Action Models as Anti-Exploration: A Test-Time Scaling Approach
- PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies
- EDT: Improving Large Language Models' Generation by Entropy-based Dynamic Temperature Sampling
- LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
- Confidence Calibration in Vision-Language-Action Models
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