Perplexity Introduces JOLT, a Post-Training Method Using One Model as Teacher and Student

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Perplexity developed JOLT, a post-training method that uses one model as both teacher and student, and said it matched GRPO’s accuracy on MATH with 6.5x fewer training tokens. In JOLT, the teacher is trained to provide feedback the student can use. The reported efficiency result applies specifically to the MATH benchmark.

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Latest development10/22 02:44 (UTC+8)

Perplexity develops JOLT, a post-training method that uses one model as teacher and student Perplexity · X

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10/22

02:44
Perplexity · X
Perplexity develops JOLT, a post-training method that uses one model as teacher and student
New research: We developed JOLT, a post-training method where one model acts as both teacher and student, with the teacher trained to give feedback the student can use. On MATH, it matched GRPO's accuracy with 6.5x fewer training tokens. https://t.co/KFHdZ0tuFn https://t.co/Y4Svd9QK4G

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