1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
Dynamic Depth Decoding: Faster Speculative Decoding for LLMs
Oscar Brown, Zhengjie Wang, Andrea Do +2
The acceleration of Large Language Models (LLMs) with speculative decoding provides a significant runtime improvement without any loss of accuracy. Currently, EAGLE-2 is the state-…
eess.AS2023
Using fine-tuning and min lookahead beam search to improve Whisper
Andrea Do, Oscar Brown, Zhengjie Wang +4
The performance of Whisper in low-resource languages is still far from perfect. In addition to a lack of training data on low-resource languages, we identify some limitations in th…