Sean Narenthiran — accepted AI-conference papers

2024

OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset

Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, Daria Gitman, Fei Jia, Igor Gitman

NeurIPS 2024oral

Recent work has shown the immense potential of synthetically generated datasets for training large language models (LLMs), especially for acquiring targeted skills. Current large-scale math instruction tuning datasets such as MetaMathQA (Yu et al., 2024) and MAmmoTH (Yue et al., 2024) are constructe…

Cited by 82 Source ↗PDF ↗code ↗Scholar ↗

2022

Torchaudio: Building Blocks for Audio and Speech Processing

Yao-Yuan Yang, Moto Hira, Zhaoheng Ni, Artyom Astafurov, Caroline Chen, Christian Puhrsch +12

ICASSP 2022accepted

This document describes version 0.10 of TorchAudio: building blocks for machine learning applications in the audio and speech processing domain. The objective of TorchAudio is to accelerate the development and deployment of machine learning applications for researchers and engineers by providing off…

Cited by 0 Source ↗Scholar ↗