Seonglae ChoVision Language Action Model
Should have action decoder or low-level vector-based controlling. If VLA generates just a high-level sequence, it is VLM not VLA
Vision Language Action Models
Vision Language Action Notion
Steering
VLA's Transformer FFN neurons still maintain semantic concepts like slow, fast, up. By selectively activating these neurons (activation steering) → robot behavior can be adjusted in real-time without fine-tuning, rewards, or environment interaction. In both simulation (OPENVLA, LIBERO) and real robots (UR5, Pi 0) → behavioral characteristics like speed and movement height change in a zero-shot manner. Semantic-based neuron intervention is more effective than prompt modification or random intervention. VLAs maintain interpretable semantic structures internally, which can be directly manipulated to control robot behavior transparently and immediately.