3 papers
cs.LG2026
KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem
Seongjin Cha, Gyuwan Kim, Dongsu Han +2
Self-speculative decoding (SSD) accelerates LLM inference by skipping layers to create an efficient draft model, yet existing methods often rely on static heuristics that ignore th…
cs.IR2026
Efficiency Optimizations for Superblock-based Sparse Retrieval
Parker Carlson, Wentai Xie, Rohil Shah +1
Learned sparse retrieval (LSR) is a popular method for first-stage retrieval because it combines the semantic matching of language models with efficient CPU-friendly algorithms. Pr…
cs.IR2025
Dynamic Superblock Pruning for Fast Learned Sparse Retrieval
Parker Carlson, Wentai Xie, Shanxiu He +1
This paper proposes superblock pruning (SP) during top-k online document retrieval for learned sparse representations. SP structures the sparse index as a set of superblocks on a s…