Interpretability that Works
Open-source suite for deep VLA interpretability. Leverage attention heatmaps, sparse autoencoders, and inference breakpoints.
Real-time Attention Maps
Visualize exactly what your model is looking at, frame by frame. Track attention patterns across visual, language, and action modalities in real-time.
Feature Circuit Analysis
Trace the flow of information through your model. Identify which neurons activate for specific behaviors and understand the computational graph.
Behavior Intervention
Directly modify model outputs in real-time. Correct undesirable actions, run counterfactual simulations, and trace issues back to training data.
Core Workflow
capture
Record comprehensive telemetry and internal model states from your VLA models.
analyze
Decode reasoning patterns and correlate neural activity with robot behaviors.
intervene
Modify behaviors and run experiments to understand model decision-making.
blog
Research updates and technical insights from the Parametric team, focusing on VLA interpretability and the future of explainable robotic AI.
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