3 citations · 4 across the 3 of their papers we have counts for
3 papers
Genetic Instruct: Scaling up Synthetic Generation of Coding Instructions for Large Language Models
Somshubra Majumdar, Vahid Noroozi, Mehrzad Samadi +6
Large Language Models (LLMs) require high quality instruction data for effective alignment, particularly in code generation tasks where expert curated datasets are expensive to pro…
Less is More: Accurate Speech Recognition & Translation without Web-Scale Data
Krishna C. Puvvada, Piotr Żelasko, He Huang +9
Recent advances in speech recognition and translation rely on hundreds of thousands of hours of Internet speech data. We argue that state-of-the art accuracy can be reached without…
Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition
Dima Rekesh, Nithin Rao Koluguri, Samuel Kriman +8
Conformer-based models have become the dominant end-to-end architecture for speech processing tasks. With the objective of enhancing the conformer architecture for efficient traini…