b'Chenyu You'

research

∙ 08/23/2023

LLMRec: Benchmarking Large Language Models on Recommendation Task

Recently, the fast development of Large Language Models (LLMs) such as C...

0 Junling Liu, et al. ∙

research

∙ 08/18/2023

Attention Calibration for Transformer-based Sequential Recommendation

Transformer-based sequential recommendation (SR) has been booming in rec...

0 Peilin Zhou, et al. ∙

research

∙ 07/05/2023

Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels

Generating an informative and attractive title for the product is a cruc...

0 Bang Yang, et al. ∙

research

∙ 06/05/2023

Benchmarking Large Language Models on CMExam – A Comprehensive Chinese Medical Exam Dataset

Recent advancements in large language models (LLMs) have transformed the...

0 Junling Liu, et al. ∙

research

∙ 05/26/2023

Large Language Models Are Partially Primed in Pronoun Interpretation

While a large body of literature suggests that large language models (LL...

0 Suet-Ying Lam, et al. ∙

research

∙ 04/06/2023

Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts

Integrating high-level semantically correlated contents and low-level an...

0 Chenyu You, et al. ∙

research

∙ 04/05/2023

ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast

Medical data often exhibits long-tail distributions with heavy class imb...

0 Chenyu You, et al. ∙

research

∙ 02/03/2023

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

For medical image segmentation, contrastive learning is the dominant pra...

0 Chenyu You, et al. ∙

research

∙ 11/22/2022

Aligning Source Visual and Target Language Domains for Unpaired Video Captioning

Training supervised video captioning model requires coupled video-captio...

0 Fenglin Liu, et al. ∙

research

∙ 10/23/2022

Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions

The "Patient Instruction" (PI), which contains critical instructional in...

0 Fenglin Liu, et al. ∙

research

∙ 09/27/2022

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels

Recent studies on contrastive learning have achieved remarkable performa...

0 Chenyu You, et al. ∙

research

∙ 09/01/2022

Learning correspondences of cardiac motion from images using biomechanics-informed modeling

Learning spatial-temporal correspondences in cardiac motion from images ...

0 Xiaoran Zhang, et al. ∙

research

∙ 07/20/2022

Flow-based Visual Quality Enhancer for Super-resolution Magnetic Resonance Spectroscopic Imaging

Magnetic Resonance Spectroscopic Imaging (MRSI) is an essential tool for...

0 Siyuan Dong, et al. ∙

research

∙ 06/17/2022

Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness

Magnetic Resonance Spectroscopic Imaging (MRSI) is a valuable tool for s...

0 Siyuan Dong, et al. ∙

research

∙ 06/10/2022

Graph-in-Graph Network for Automatic Gene Ontology Description Generation

Gene Ontology (GO) is the primary gene function knowledge base that enab...

0 Fenglin Liu, et al. ∙

research

∙ 06/07/2022

MIRNF: Medical Image Registration via Neural Fields

Image registration is widely used in medical image analysis to provide s...

16 Shanlin Sun, et al. ∙

research

∙ 06/06/2022

Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation

Contrastive learning has shown great promise over annotation scarcity pr...

0 Chenyu You, et al. ∙

research

∙ 06/03/2022

Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation

Many medical datasets have recently been created for medical image segme...

0 Chenyu You, et al. ∙

research

∙ 01/26/2022

Class-Aware Generative Adversarial Transformers for Medical Image Segmentation

Transformers have made remarkable progress towards modeling long-range d...

0 Chenyu You, et al. ∙

research

∙ 01/03/2022

KerGNNs: Interpretable Graph Neural Networks with Graph Kernels

Graph kernels are historically the most widely-used technique for graph ...

12 Aosong Feng, et al. ∙

research

∙ 11/08/2021

Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation

Medical report generation, which aims to automatically generate a long a...

17 Fenglin Liu, et al. ∙

research

∙ 10/28/2021

MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution

Space-time video super-resolution (STVSR) aims to construct a high space...

4 Chenyu You, et al. ∙

research

∙ 08/13/2021

SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation

Automated segmentation in medical image analysis is a challenging task t...

10 Chenyu You, et al. ∙

research

∙ 06/04/2021

Self-supervised Dialogue Learning for Spoken Conversational Question Answering

In spoken conversational question answering (SCQA), the answer to the co...

0 Nuo Chen, et al. ∙

research

∙ 05/16/2021

Undistillable: Making A Nasty Teacher That CANNOT teach students

Knowledge Distillation (KD) is a widely used technique to transfer knowl...

32 Haoyu Ma, et al. ∙

research

∙ 05/14/2021

Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation

Automated segmentation in medical image analysis is a challenging task t...

0 Chenyu You, et al. ∙

research

∙ 01/08/2021

Good Students Play Big Lottery Better

Lottery ticket hypothesis suggests that a dense neural network contains ...

3 Haoyu Ma, et al. ∙

research

∙ 12/20/2020

Adaptive Bi-directional Attention: Exploring Multi-Granularity Representations for Machine Reading Comprehension

Recently, the attention-enhanced multi-layer encoder, such as Transforme...

0 Nuo Chen, et al. ∙

research

∙ 10/21/2020

Knowledge Distillation for Improved Accuracy in Spoken Question Answering

Spoken question answering (SQA) is a challenging task that requires the ...

0 Chenyu You, et al. ∙

research

∙ 10/21/2020

Contextualized Attention-based Knowledge Transfer for Spoken Conversational Question Answering

Spoken conversational question answering (SCQA) requires machines to mod...

0 Chenyu You, et al. ∙

research

∙ 10/18/2020

Towards Data Distillation for End-to-end Spoken Conversational Question Answering

In spoken question answering, QA systems are designed to answer question...

0 Chenyu You, et al. ∙

research

∙ 09/06/2020

Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation

Deep neural networks have shown exceptional learning capability and gene...

8 Chenyu You, et al. ∙

research

∙ 11/26/2018

Low-Dose CT via Deep CNN with Skip Connection and Network in Network

A major challenge in computed tomography (CT) is how to minimize patient...

8 Chenyu You, et al. ∙

research

∙ 08/10/2018

CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)

Computed tomography (CT) is a popular medical imaging modality for scree...

0 Chenyu You, et al. ∙

research

∙ 05/02/2018

Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising

Computed tomography (CT) is a popular medical imaging modality in clinic...

0 Chenyu You, et al. ∙

Chenyu You

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