1 code implementation • Findings (EMNLP) 2021 • Nan Bai, Renqian Luo, Pirouz Nourian, Ana Pereira Roders
A human study with expert evaluation on the model prediction shows that the models are sufficiently generalizable.
2 code implementations • 28 Nov 2023 • Harsha Nori, Yin Tat Lee, Sheng Zhang, Dean Carignan, Richard Edgar, Nicolo Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, Weishung Liu, Renqian Luo, Scott Mayer McKinney, Robert Osazuwa Ness, Hoifung Poon, Tao Qin, Naoto Usuyama, Chris White, Eric Horvitz
We find that prompting innovation can unlock deeper specialist capabilities and show that GPT-4 easily tops prior leading results for medical benchmarks.
Ranked #2 on Question Answering on MedQA (using extra training data)
3 code implementations • 19 Oct 2022 • Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu
Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain.
Ranked #1 on Document Classification on HOC (Micro F1 metric)
no code implementations • 29 Aug 2021 • Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li
In this paper, we investigate the interference issue by sampling different child models and calculating the gradient similarity of shared operators, and observe: 1) the interference on a shared operator between two child models is positively correlated with the number of different operators; 2) the interference is smaller when the inputs and outputs of the shared operator are more similar.
no code implementations • 9 Jul 2021 • Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu
Neural approaches have achieved state-of-the-art accuracy on machine translation but suffer from the high cost of collecting large scale parallel data.
Low Resource Neural Machine Translation Low-Resource Neural Machine Translation +4
no code implementations • 30 May 2021 • Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu
The technical challenge of NAS-BERT is that training a big supernet on the pre-training task is extremely costly.
1 code implementation • NeurIPS 2021 • Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiang-Yang Li, Ed Lin, Tie-Yan Liu
A straightforward solution to reduce latency, inspired by non-autoregressive (NAR) neural machine translation, is to use an NAR sequence generation model for ASR error correction, which, however, comes at the cost of significantly increased ASR error rate.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
1 code implementation • 12 Apr 2021 • Nan Bai, Renqian Luo, Pirouz Nourian, Ana Pereira Roders
A human study with expert evaluation on the model prediction shows that the models are sufficiently generalizable.
4 code implementations • 8 Feb 2021 • Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu
Text to speech (TTS) has been broadly used to synthesize natural and intelligible speech in different scenarios.
no code implementations • 1 Jan 2021 • Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Li Jian, Tao Qin, Tie-Yan Liu
NAS-BERT trains a big supernet on a carefully designed search space containing various architectures and outputs multiple compressed models with adaptive sizes and latency.
1 code implementation • 9 Jul 2020 • Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu
Considering that most architectures are represented as sequences of discrete symbols which are more like tabular data and preferred by non-neural predictors, in this paper, we study an alternative approach which uses non-neural model for accuracy prediction.
Ranked #81 on Neural Architecture Search on ImageNet
2 code implementations • NeurIPS 2020 • Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu
On ImageNet, it achieves 23. 5% top-1 error rate (under 600M FLOPS constraint) using 4 GPU-days for search.
Ranked #81 on Neural Architecture Search on ImageNet
no code implementations • WS 2019 • Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, Tie-Yan Liu
We Microsoft Research Asia made submissions to 11 language directions in the WMT19 news translation tasks.
1 code implementation • 24 Sep 2019 • Renqian Luo, Tao Qin, Enhong Chen
One-shot NAS is proposed to reduce the expense but shows inferior performance against conventional NAS and is not adequately stable.
5 code implementations • NeurIPS 2018 • Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, Tie-Yan Liu
The performance predictor and the encoder enable us to perform gradient based optimization in the continuous space to find the embedding of a new architecture with potentially better accuracy.
2 code implementations • 15 Mar 2018 • Hany Hassan, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt, William Lewis, Mu Li, Shujie Liu, Tie-Yan Liu, Renqian Luo, Arul Menezes, Tao Qin, Frank Seide, Xu Tan, Fei Tian, Lijun Wu, Shuangzhi Wu, Yingce Xia, Dong-dong Zhang, Zhirui Zhang, Ming Zhou
Machine translation has made rapid advances in recent years.
Ranked #3 on Machine Translation on WMT 2017 English-Chinese