CausGround distills causal action knowledge from interaction to improve embodied planning without retraining
Yijun Shen · hf · 2026-10-29
A paper from ECNU, BAAI, NWPU and others introduces CausGround, a non-parametric causal interaction grounding framework for embodied planning.
- Problem: MLLMs reason well but can't reliably judge when actions are executable and how they change the world; existing adaptation needs costly environment-specific training or yields unstructured, hard-to-reuse experience
- Method: distills interaction experience into reusable action-centered causal knowledge by identifying action preconditions and effects
- Result: improves embodied planning and reasoning across diverse environments without model retraining
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