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Self-evolving agents are usually scored by endpoint Gain: held-out success after an update minus success before. That difference can credit a frozen rescore as evolution. We introduce Trace Evolution Bench (TEB), a protocol that separates that rescore from a context or weight update, together with three frozen 80/20/40...
Vision-based reinforcement learning has emerged as a promising approach for autonomous robotic control. It enables closed-loop policy learning directly from high-dimensional visual observations. However, existing methods often learn visual representations through prediction or reconstruction objectives, which may prese...
This work proposes a safe offline-to-online decision-making framework with adaptive causal representation, an adaptive causal transformer (AC-Transformer), which learns a causal representation from offline driving trajectories that is adaptive as the deployment distribution evolves.
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