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CoreSense: Traceable Failure Recall and Conflict-Aware Belief Gating for Auditable Robot Decisions

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Robots can recall prior failures without knowing whether recalled evidence remains valid, conflicts with current observations, or is sufficient to guide a decision. We present CoreSense, a robot-system integration architecture that combines traceable episodic evidence with a conflict-aware belief gate and bounded, auditable recommendations. The gate checks scope, provenance, time, contradiction, and support before it permits PROCEED, requests re-observation, abstains, or escalates. Evaluation follows three complementary layers without commanding a physical robot: offline public real-robot data

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