1.6k citations · 4.2k across the 75 of their papers we have counts for
3 papers · 2 filters
dMel: Speech Tokenization made Simple
Richard He Bai, Tatiana Likhomanenko, Ruixiang Zhang +3
Large language models have revolutionized natural language processing by leveraging self-supervised pretraining on vast textual data. Inspired by this success, researchers have inv…
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Zhuofeng Wu, He Bai, Aonan Zhang +4
Recent methods have demonstrated that Large Language Models (LLMs) can solve reasoning tasks better when they are encouraged to solve subtasks of the main task first. In this paper…
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Pratyush Maini, Skyler Seto, He Bai +3
Large language models are trained on massive scrapes of the web, which are often unstructured, noisy, and poorly phrased. Current scaling laws show that learning from such data req…