64 citations · 85 across the 22 of their papers we have counts for
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cs.DC2026
Speculation at a Distance: Where Edge-Cloud Speculative Decoding Actually Pays Off
Yuan Lyu, Bharath Irukulapati, Jaya Prakash Champati
Speculative decoding (SD) accelerates LLM inference by - times when the draft and target models are co-located. This has motivated a distributed variant (DSD) that places t…
cs.LG2026
Pay for Hints, Not Answers: LLM Shepherding for Cost-Efficient Inference
Ziming Dong, Hardik Sharma, Evan O'Toole +2
Large Language Models (LLMs) deliver state-of-the-art performance on complex reasoning tasks, but their inference costs limit deployment at scale. Small Language Models (SLMs) offe…