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News/TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels
arxiv
PublishedJuly 1, 2026 at 4:00 AM
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TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels

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arXiv:2504.12557v3 Announce Type: replace-cross Abstract: Ensuring safe behavior in reinforcement learning (RL) is challenging when safety constraints are implicit and cannot be densely measured. In many settings, supervision is limited to coarse approvals or rejections of whole trajectories (e.g.,

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