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On-policy self-distillation (OPSD) supplies dense token-level feedback on trajectories sampled from the student's own policy, a richer training signal than the outcome-level rewards of reinforcement learning. This feedback comes from a teacher conditioned on a full reference solution unavailable to the student. The ref...
CCubicSplat is a differentiable vector rasterizer that replaces B\'ezier closest-point solvers with uniform polyline surrogates whose geometric error is bounded at $O(S^{-2})$.
This work proposes Step-wise Training for In-context Reasoning (STIR), a model to dynamically decide when to retrieve a single logically consistent next step, just using the current problem and its intermediate state as the query.
This work proposes Step-wise Training for In-context Reasoning (STIR), a model to dynamically decide when to retrieve a single logically consistent next step, just using the current problem and its intermediate state as the query.
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