Article

ConfigWM: Configurable-Perception World Models via Task-Conditioned State Extraction

ConfigWM proposes a configurable perception mechanism that uses task language descriptions as configuration signals to guide the mapping of visual embeddings into task-specific state spaces, selectively retaining task-relevant information and suppressing distractions. In environments with progressively increasing distraction, existing methods show a marked decline in planning success rate, while ConfigWM remains relatively stable, averaging 22.3% higher than the strongest competing method. Physical-quantity probing (Pearson r +0.365) and distracted-to-clean retrieval (+75.5%) also show consistent improvements.

Part of the event: ConfigWM: A Configurable Perception World Model for Task-Conditioned State Extraction

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