no code implementations • 29 Apr 2022 • Chenyu You, Nuo Chen, Fenglin Liu, Shen Ge, Xian Wu, Yuexian Zou
To evaluate the capacity of SCQA systems in a dialogue-style interaction, we assemble a Spoken Conversational Question Answering (Spoken-CoQA) dataset with more than 40k question-answer pairs from 4k conversations.
no code implementations • 26 Jan 2022 • Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence Staib, James S. Duncan
In this work, we present CASTformer, a novel type of generative adversarial transformers, for 2D medical image segmentation.
1 code implementation • 3 Jan 2022 • Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas
We also show that the trained graph filters in KerGNNs can reveal the local graph structures of the dataset, which significantly improves the model interpretability compared with conventional GNN models.
no code implementations • NeurIPS 2021 • Fenglin Liu, Chenyu You, Xian Wu, Shen Ge, Sheng Wang, Xu sun
KGAE consists of a pre-constructed knowledge graph, a knowledge-driven encoder and a knowledge-driven decoder.
no code implementations • 28 Oct 2021 • Chenyu You, Lianyi Han, Aosong Feng, Ruihan Zhao, Hui Tang, Wei Fan
Space-time video super-resolution (STVSR) aims to construct a high space-time resolution video sequence from the corresponding low-frame-rate, low-resolution video sequence.
no code implementations • 29 Sep 2021 • Haoyu Ma, Yifan Huang, Tianlong Chen, Hao Tang, Chenyu You, Zhangyang Wang, Xiaohui Xie
However, it is unclear why the distorted distribution of the logits is catastrophic to the student model.
no code implementations • Findings (EMNLP) 2021 • Chenyu You, Nuo Chen, Yuexian Zou
In this paper, we propose novel training schemes for spoken question answering with a self-supervised training stage and a contrastive representation learning stage.
no code implementations • 13 Aug 2021 • Chenyu You, Yuan Zhou, Ruihan Zhao, Lawrence Staib, James S. Duncan
However, most existing learning-based approaches usually suffer from limited manually annotated medical data, which poses a major practical problem for accurate and robust medical image segmentation.
no code implementations • 4 Jun 2021 • Nuo Chen, Chenyu You, Yuexian Zou
We also utilize the proposed self-supervised learning tasks to capture intra-sentence coherence.
1 code implementation • ICLR 2021 • Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Knowledge Distillation (KD) is a widely used technique to transfer knowledge from pre-trained teacher models to (usually more lightweight) student models.
no code implementations • 14 May 2021 • Chenyu You, Ruihan Zhao, Lawrence Staib, James S. Duncan
In this work, we present a novel Contrastive Voxel-wise Representation Learning (CVRL) method to effectively learn low-level and high-level features by capturing 3D spatial context and rich anatomical information along both the feature and the batch dimensions.
no code implementations • 20 Dec 2020 • Nuo Chen, Fenglin Liu, Chenyu You, Peilin Zhou, Yuexian Zou
To predict the answer, it is common practice to employ a predictor to draw information only from the final encoder layer which generates the \textit{coarse-grained} representations of the source sequences, i. e., passage and question.
no code implementations • 21 Oct 2020 • Chenyu You, Nuo Chen, Yuexian Zou
Spoken conversational question answering (SCQA) requires machines to model complex dialogue flow given the speech utterances and text corpora.
Audio Signal Processing
Conversational Question Answering
+2
no code implementations • 21 Oct 2020 • Chenyu You, Nuo Chen, Yuexian Zou
However, the recent work shows that ASR systems generate highly noisy transcripts, which critically limit the capability of machine comprehension on the SQA task.
no code implementations • 18 Oct 2020 • Chenyu You, Nuo Chen, Fenglin Liu, Dongchao Yang, Yuexian Zou
In spoken question answering, QA systems are designed to answer questions from contiguous text spans within the related speech transcripts.
Automatic Speech Recognition
Conversational Question Answering
no code implementations • 6 Sep 2020 • Chenyu You, Junlin Yang, Julius Chapiro, James S. Duncan
However, the well-trained models often fail in the target domain due to the domain shift.
no code implementations • 16 May 2020 • Fenglin Liu, Xuancheng Ren, Guangxiang Zhao, Chenyu You, Xian Wu, Xu sun
While it is common practice to draw information from only the last encoder layer, recent work has proposed to use representations from different encoder layers for diversified levels of information.
no code implementations • 26 Nov 2018 • Chenyu You, Linfeng Yang, Yi Zhang, Ge Wang
The use of deep convolutional (Conv) neural networks for noise reduction in Low-Dose CT (LDCT) images has recently shown a great potential in this important application.
no code implementations • 16 Oct 2018 • Qing Lyu, Chenyu You, Hongming Shan, Ge Wang
Magnetic resonance imaging (MRI) is extensively used for diagnosis and image-guided therapeutics.
Medical Physics
no code implementations • 10 Aug 2018 • Chenyu You, Guang Li, Yi Zhang, Xiaoliu Zhang, Hongming Shan, Shenghong Ju, Zhen Zhao, Zhuiyang Zhang, Wenxiang Cong, Michael W. Vannier, Punam K. Saha, Ge Wang
Specifically, with the generative adversarial network (GAN) as the building block, we enforce the cycle-consistency in terms of the Wasserstein distance to establish a nonlinear end-to-end mapping from noisy LR input images to denoised and deblurred HR outputs.
no code implementations • 2 May 2018 • Chenyu You, Qingsong Yang, Hongming Shan, Lars Gjesteby, Guang Li, Shenghong Ju, Zhuiyang Zhang, Zhen Zhao, Yi Zhang, Wenxiang Cong, Ge Wang
However, the radiation dose reduction compromises the signal-to-noise ratio (SNR), leading to strong noise and artifacts that down-grade CT image quality.