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20232026
most citedA Survey of Techniques for Optimizing Transformer Inference

8 citations · 10 across the 12 of their papers we have counts for

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2 papers · 1 filter

cs.LG2026

H-Spec: Parallel Speculative Decoding Without a Drafter-Side KV Cache

Weifan Jiang, Krishna Teja Chitty-Venkata, Megan Flynn +6

Speculative decoding losslessly accelerates large language model inference by having a lightweight draft model predict future tokens for verification by the target model. Recent bl…

cs.LG2026

Swimba: Switch Mamba Model Scales State Space Models

Zhixu Du, Krishna Teja Chitty-Venkata, Murali Emani +3

Mixture-of-experts (MoE) is a common approach for increasing parameter capacity, but applying MoE to state space model (SSM) token mixers can multiply the cost of the recurrent sta…