Search Results for author: Yuhao Wang

Found 43 papers, 24 papers with code

TextBox 2.0: A Text Generation Library with Pre-trained Language Models

1 code implementation26 Dec 2022 Tianyi Tang, Junyi Li, Zhipeng Chen, Yiwen Hu, Zhuohao Yu, Wenxun Dai, Zican Dong, Xiaoxue Cheng, Yuhao Wang, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen

To facilitate research on text generation, this paper presents a comprehensive and unified library, TextBox 2. 0, focusing on the use of pre-trained language models (PLMs).

Abstractive Text Summarization Data-to-Text Generation +7

Learning in the Frequency Domain

4 code implementations CVPR 2020 Kai Xu, Minghai Qin, Fei Sun, Yuhao Wang, Yen-Kuang Chen, Fengbo Ren

Experiment results show that learning in the frequency domain with static channel selection can achieve higher accuracy than the conventional spatial downsampling approach and meanwhile further reduce the input data size.

Instance Segmentation Semantic Segmentation

Scientific Large Language Models: A Survey on Biological & Chemical Domains

1 code implementation26 Jan 2024 Qiang Zhang, Keyang Ding, Tianwen Lyv, Xinda Wang, Qingyu Yin, Yiwen Zhang, Jing Yu, Yuhao Wang, Xiaotong Li, Zhuoyi Xiang, Xiang Zhuang, Zeyuan Wang, Ming Qin, Mengyao Zhang, Jinlu Zhang, Jiyu Cui, Renjun Xu, Hongyang Chen, Xiaohui Fan, Huabin Xing, Huajun Chen

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence.

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation

1 code implementation20 Jul 2023 Ruiyang Ren, Yuhao Wang, Yingqi Qu, Wayne Xin Zhao, Jing Liu, Hao Tian, Hua Wu, Ji-Rong Wen, Haifeng Wang

In this study, we present an initial analysis of the factual knowledge boundaries of LLMs and how retrieval augmentation affects LLMs on open-domain QA.

Open-Domain Question Answering Retrieval +1

TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation

1 code implementation15 Dec 2023 Yuhao Wang, Xuehu Liu, Pingping Zhang, Hu Lu, Zhengzheng Tu, Huchuan Lu

In addition, most of current Transformer-based ReID methods only utilize the global feature of class tokens to achieve the holistic retrieval, ignoring the local discriminative ones.

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

1 code implementation15 Mar 2024 Pingping Zhang, Yuhao Wang, Yang Liu, Zhengzheng Tu, Huchuan Lu

To address above issues, we propose a novel learning framework named \textbf{EDITOR} to select diverse tokens from vision Transformers for multi-modal object ReID.

Object

Joint Intensity-Gradient Guided Generative Modeling for Colorization

6 code implementations28 Dec 2020 Kai Hong, Jin Li, Wanyun Li, Cailian Yang, Minghui Zhang, Yuhao Wang, Qiegen Liu

Furthermore, the joint intensity-gradient constraint in data-fidelity term is proposed to limit the degree of freedom within generative model at the iterative colorization stage, and it is conducive to edge-preserving.

Colorization

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization

4 code implementations9 Jul 2021 Jin Li, Wanyun Li, Zichen Xu, Yuhao Wang, Qiegen Liu

Unsupervised deep learning has recently demonstrated the promise of producing high-quality samples.

Colorization Denoising +1

REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering

1 code implementation27 Feb 2024 Yuhao Wang, Ruiyang Ren, Junyi Li, Wayne Xin Zhao, Jing Liu, Ji-Rong Wen

By combining the improvements in both architecture and training, our proposed REAR can better utilize external knowledge by effectively perceiving the relevance of retrieved documents.

Open-Domain Question Answering Retrieval

Direct Estimation of Differences in Causal Graphs

1 code implementation NeurIPS 2018 Yuhao Wang, Chandler Squires, Anastasiya Belyaeva, Caroline Uhler

We consider the problem of estimating the differences between two causal directed acyclic graph (DAG) models given i. i. d.~samples from each model.

Methodology

Exploration and Regularization of the Latent Action Space in Recommendation

1 code implementation7 Feb 2023 Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Kun Gai, Peng Jiang, Xiangyu Zhao, Yongfeng Zhang

To overcome this challenge, we propose a hyper-actor and critic learning framework where the policy decomposes the item list generation process into a hyper-action inference step and an effect-action selection step.

Recommendation Systems

Learning Priors in High-frequency Domain for Inverse Imaging Reconstruction

1 code implementation23 Oct 2019 Zhuonan He, Jinjie Zhou, Dong Liang, Yuhao Wang, Qiegen Liu

Ill-posed inverse problems in imaging remain an active research topic in several decades, with new approaches constantly emerging.

Denoising Dictionary Learning +1

Generative Modeling in Structural-Hankel Domain for Color Image Inpainting

1 code implementation25 Nov 2022 Zihao Li, CHUNHUA WU, Shenglin Wu, Wenbo Wan, Yuhao Wang, Qiegen Liu

To better apply the score-based generative model to learn the internal statistical distribution within patches, the large-scale Hankel matrices are finally folded into the higher dimensional tensors for prior learning.

Image Inpainting

Learning Sparse Fixed-Structure Gaussian Bayesian Networks

1 code implementation22 Jul 2021 Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang

We also study a couple of new algorithms for the problem: - BatchAvgLeastSquares takes the average of several batches of least squares solutions at each node, so that one can interpolate between the batch size and the number of batches.

MRI Reconstruction Using Deep Energy-Based Model

1 code implementation7 Sep 2021 Yu Guan, Zongjiang Tu, Shanshan Wang, Qiegen Liu, Yuhao Wang, Dong Liang

In contrast to other generative models for reconstruction, the proposed method utilizes deep energy-based information as the image prior in reconstruction to improve the quality of image.

Image Generation MRI Reconstruction

Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction

1 code implementation25 Nov 2022 Bing Guan, Cailian Yang, Liu Zhang, Shanzhou Niu, Minghui Zhang, Yuhao Wang, Weiwen Wu, Qiegen Liu

When the number of projection view changes, the DL network should be retrained with updated sparse-view/full-view CT image pairs.

Computed Tomography (CT) Image Reconstruction

MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

1 code implementation15 Jan 2024 Yuhao Wang, Yusheng Liao, Heyang Liu, Hongcheng Liu, Yu Wang, Yanfeng Wang

We believe that these hallucinations are partially due to the models' struggle with understanding what they can and cannot perceive from images, a capability we refer to as self-awareness in perception.

High-dimensional Assisted Generative Model for Color Image Restoration

1 code implementation14 Aug 2021 Kai Hong, CHUNHUA WU, Cailian Yang, Minghui Zhang, Yancheng Lu, Yuhao Wang, Qiegen Liu

This work presents an unsupervised deep learning scheme that exploiting high-dimensional assisted score-based generative model for color image restoration tasks.

Demosaicking Denoising +1

Variable Augmented Network for Invertible Modality Synthesis-Fusion

1 code implementation2 Sep 2021 Yuhao Wang, Ruirui Liu, Zihao Li, Cailian Yang, Qiegen Liu

As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinical applications such as disease diagnosis and treatment planning.

Image Generation

Direction-Aggregated Attack for Transferable Adversarial Examples

1 code implementation19 Apr 2021 Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy

Deep neural networks are vulnerable to adversarial examples that are crafted by imposing imperceptible changes to the inputs.

Amortized Variational Deep Q Network

1 code implementation3 Nov 2020 Haotian Zhang, Yuhao Wang, Jianyong Sun, Zongben Xu

Efficient exploration is one of the most important issues in deep reinforcement learning.

Efficient Exploration OpenAI Gym +1

Identifiability of AMP chain graph models

1 code implementation17 Jun 2021 Yuhao Wang, Arnab Bhattacharyya

AMP models are described by DAGs on chain components which themselves are undirected graphs.

Permutation-based Causal Inference Algorithms with Interventions

no code implementations NeurIPS 2017 Yuhao Wang, Liam Solus, Karren Yang, Caroline Uhler

Learning directed acyclic graphs using both observational and interventional data is now a fundamentally important problem due to recent technological developments in genomics that generate such single-cell gene expression data at a very large scale.

Causal Inference

DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks

no code implementations19 Nov 2019 Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-Kuang Chen, Yuan Xie, Yanzhi Wang

As a further optimization, we propose a density-adaptive regular-block (DARB) pruning that outperforms prior structured pruning work with high pruning ratio and decoding efficiency.

Model Compression Network Pruning

Causal Discovery from Incomplete Data: A Deep Learning Approach

no code implementations15 Jan 2020 Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy

As systems are getting more autonomous with the development of artificial intelligence, it is important to discover the causal knowledge from observational sensory inputs.

Causal Discovery Imputation

Joint Inference of Multiple Graphs from Matrix Polynomials

no code implementations16 Oct 2020 Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra

Inferring graph structure from observations on the nodes is an important and popular network science task.

Sparse Code Multiple Access for 6G Wireless Communication Networks: Recent Advances and Future Directions

no code implementations3 Apr 2021 Lisu Yu, Zilong Liu, Miaowen Wen, Donghong Cai, Shuping Dang, Yuhao Wang, Pei Xiao

As 5G networks rolling out in many different countries nowadays, the time has come to investigate how to upgrade and expand them towards 6G, where the latter is expected to realize the interconnection of everything as well as the development of a ubiquitous intelligent mobile world for intelligent life.

Virtual Coil Augmentation Technology for MR Coil Extrapolation via Deep Learning

no code implementations19 Jan 2022 Cailian Yang, Xianghao Liao, Yuhao Wang, Minghui Zhang, Qiegen Liu

Two main components are incorporated into the network design, namely variable augmentation technology and sum of squares (SOS) objective function.

Image Reconstruction Super-Resolution

Variable Augmented Network for Invertible MR Coil Compression

1 code implementation19 Jan 2022 Xianghao Liao, Shanshan Wang, Lanlan Tu, Yuhao Wang, Dong Liang, Qiegen Liu

Additionally, its performance is not susceptible to different number of virtual coils.

Long-term Causal Inference Under Persistent Confounding via Data Combination

no code implementations15 Feb 2022 Guido Imbens, Nathan Kallus, Xiaojie Mao, Yuhao Wang

In this paper, we uniquely tackle the challenge of persistent unmeasured confounders, i. e., some unmeasured confounders that can simultaneously affect the treatment, short-term outcomes and the long-term outcome, noting that they invalidate identification strategies in previous literature.

Causal Inference

Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs

no code implementations24 Jun 2022 Yifan Lin, Yuhao Wang, Enlu Zhou

In particular, we consider mean-variance as the risk criterion, and the best arm is the one with the largest mean-variance reward.

Thompson Sampling

Factorized Blank Thresholding for Improved Runtime Efficiency of Neural Transducers

no code implementations2 Nov 2022 Duc Le, Frank Seide, Yuhao Wang, Yang Li, Kjell Schubert, Ozlem Kalinli, Michael L. Seltzer

We show how factoring the RNN-T's output distribution can significantly reduce the computation cost and power consumption for on-device ASR inference with no loss in accuracy.

Self adaptive global-local feature enhancement for radiology report generation

no code implementations21 Nov 2022 Yuhao Wang, Kai Wang, Xiaohong Liu, Tianrun Gao, Jingyue Zhang, Guangyu Wang

Automated radiology report generation aims at automatically generating a detailed description of medical images, which can greatly alleviate the workload of radiologists and provide better medical services to remote areas.

Anatomy

Multi-Task Deep Recommender Systems: A Survey

no code implementations7 Feb 2023 Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang

Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual improvement among tasks considering their shared knowledge.

Multi-Task Learning Recommendation Systems +1

SelfEvolve: A Code Evolution Framework via Large Language Models

no code implementations5 Jun 2023 Shuyang Jiang, Yuhao Wang, Yu Wang

However, while various methods have been proposed to augment LLMs with retrieved knowledge and enhance the quality of code generation, the performance of these retrieval-based methods is limited by the strength of the retrievers used.

Code Generation Retrieval

Reading Radiology Imaging Like The Radiologist

no code implementations12 Jul 2023 Yuhao Wang

By referencing the disease-oriented similar report and the visual features, the factual consistency model can generate a more accurate radiology report.

Image Captioning Retrieval +1

Unified Medical Image-Text-Label Contrastive Learning With Continuous Prompt

no code implementations12 Jul 2023 Yuhao Wang

In this paper, we propose a unified Image-Text-Label contrastive learning framework based on continuous prompts, with three main contributions.

Contrastive Learning

Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation

no code implementations5 Sep 2023 Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang

To address these limitations, we propose a Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendations (HierRec), which perceives implicit patterns adaptively and conducts explicit and implicit scenario modeling jointly.

Click-Through Rate Prediction

Optimal estimation of Gaussian (poly)trees

1 code implementation9 Feb 2024 Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya

We develop optimal algorithms for learning undirected Gaussian trees and directed Gaussian polytrees from data.

Infrared and visible Image Fusion with Language-driven Loss in CLIP Embedding Space

no code implementations26 Feb 2024 Yuhao Wang, Lingjuan Miao, Zhiqiang Zhou, Lei Zhang, Yajun Qiao

A language-driven fusion model is then constructed in the embedding space, by establishing the relationship among the embedded vectors to represent the fusion objective and input image modalities.

Infrared And Visible Image Fusion

Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate

no code implementations1 Mar 2024 Yifan Lin, Yuhao Wang, Enlu Zhou

The efficient utilization of historical trajectories obtained from previous policies is essential for expediting policy optimization.

Policy Gradient Methods

Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulator

no code implementations13 Mar 2024 Yusheng Liao, Yutong Meng, Yuhao Wang, Hongcheng Liu, Yanfeng Wang, Yu Wang

Large Language Models (LLMs) have demonstrated remarkable proficiency in human interactions, yet their application within the medical field remains insufficiently explored.

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