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cs.LG2026
LLM Evaluation is a Forecasting Problem
Rahul Thomas, Adam Block, Micah Goldblum
Standard procedure in machine learning is to randomly split train and test data, emulating IID draws from one underlying data distribution. In practice, models are trained on past…
cs.LG2026
Dynamic Delayed Tree Expansion For Improved Multi-Path Speculative Decoding
Rahul Thomas, Teo Kitanovski, Micah Goldblum +1
Multi-path speculative decoding accelerates lossless sampling from a target model by using a cheaper draft model to generate a draft tree of tokens, and then applies a verification…
cs.IT2026
Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling
Rahul Thomas, Arka Pal, David Hidary
The goal of -step speculative decoding is to accelerate autoregressive decoding of a target model by using a cheaper draft model to generate a candidate path of tokens. Base…