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Introducing AutoJudge: Streamlined inference acceleration via automated dataset curation
AutoJudge releases a speculative decoding method that uses a lightweight classifier to accept up to 40 draft tokens per cycle, achieving 1.5–2× inference speedups with minimal accuracy loss.
AutoJudge accelerates LLM inference by identifying which token mismatches actually matter. Using self-supervised learning to train a lightweight classifier, it accepts up to 40 draft tokens per cycle—delivering 1.5–2× speedups over standard speculative decoding with minimal accur
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