Unverified50% confidenceFactExact time
SPTA does not change the distillation objective itself, and only improves the reliability of the supervision signal through teacher adaptation.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
11/3/2026
First Seen
Valid until: 2/1/2027
Sources
Related Entities
Related Claims
UnverifiedSPTA achieves better results than standard OPD and task-level RLVR-adapted teachers on math reasoning benchmarks.66% similarUnverifiedOPD does not require task success/failure reward signals and relies only on the teacher's token-by-token supervision, so it is a reward-free method.64% similarUnverifiedThe frequency-aware training schedule adds no model parameters and does not change inference-time computation, making it a purely training-side improvement.61% similarUnverifiedJOLT's design eliminates the overhead of maintaining two sets of parameters and lets the teacher signal evolve in sync with the student policy, avoiding the teacher lagging behind the student's current capability level due to being frozen.60% similarUnverifiedSeTPO introduces teacher signals only for low-reward trajectories, uses reverse KL divergence to derive token-level teacher feedback, and incorporates it into the policy advantage function.60% similar
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