AI RESEARCH
AdaSD: Adaptive Speculative Decoding for Efficient Language Model Inference
arXiv CS.CL
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ArXi:2512.11280v2 Announce Type: replace Large language models (LLMs) have achieved remarkable performance across a wide range of tasks, but their increasing parameter sizes significantly slow down inference. Speculative decoding mitigates this issue by leveraging a smaller draft model to predict candidate tokens, which are then verified by a larger target model. However, existing approaches often require additional