SD-Zero converts binary rewards into dense self-supervision by having a model revise its own outputs and distill the improvements back into generation, yielding at least 10% gains on math and code benchmarks.
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Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision
SD-Zero converts binary rewards into dense self-supervision by having a model revise its own outputs and distill the improvements back into generation, yielding at least 10% gains on math and code benchmarks.