Search Results for author: Fei Wang

Found 306 papers, 130 papers with code

Local Correlation Consistency for Knowledge Distillation

no code implementations ECCV 2020 Xiaojie Li, Jianlong Wu, Hongyu Fang, Yue Liao, Fei Wang, Chen Qian

Sufficient knowledge extraction from the teacher network plays a critical role in the knowledge distillation task to improve the performance of the student network.

Knowledge Distillation

A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions

no code implementations7 Jul 2024 Fei Wang, Weibo Gao, Qi Liu, Jiatong Li, Guanhao Zhao, Zheng Zhang, Zhenya Huang, Mengxiao Zhu, Shijin Wang, Wei Tong, Enhong Chen

Cognitive diagnosis has been developed for decades as an effective measurement tool to evaluate human cognitive status such as ability level and knowledge mastery.

cognitive diagnosis

Micro-gesture Online Recognition using Learnable Query Points

no code implementations5 Jul 2024 Pengyu Liu, Fei Wang, Kun Li, Guoliang Chen, Yanyan Wei, Shengeng Tang, Zhiliang Wu, Dan Guo

The Micro-gesture Online Recognition task involves identifying the category and locating the start and end times of micro-gestures in video clips.

Action Detection

From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning

no code implementations1 Jul 2024 Nan Xu, Fei Wang, Sheng Zhang, Hoifung Poon, Muhao Chen

Motivated by in-context learning (ICL) capabilities of Large Language models (LLMs), multimodal LLMs with additional visual modality are also exhibited with similar ICL abilities when multiple image-text pairs are provided as demonstrations.

In-Context Learning

OpenMaterial: A Comprehensive Dataset of Complex Materials for 3D Reconstruction

no code implementations13 Jun 2024 Zheng Dang, Jialu Huang, Fei Wang, Mathieu Salzmann

Recent advances in deep learning such as neural radiance fields and implicit neural representations have significantly propelled the field of 3D reconstruction.

3D Reconstruction

Faces of the Mind: Unveiling Mental Health States Through Facial Expressions in 11,427 Adolescents

1 code implementation30 May 2024 Xiao Xu, Keyin Zhou, Yan Zhang, Yang Wang, Fei Wang, Xizhe Zhang

Mood disorders, including depression and anxiety, often manifest through facial expressions.

Module control of network analysis in psychopathology

no code implementations30 May 2024 Chunyu Pan, Quan Zhang, Yue Zhu, Shengzhou Kong, Juan Liu, Changsheng Zhang, Fei Wang, Xizhe Zhang

The network approach to characterizing psychopathology departs from traditional latent categorical and dimensional approaches.

Yuan 2.0-M32: Mixture of Experts with Attention Router

1 code implementation28 May 2024 Shaohua Wu, Jiangang Luo, Xi Chen, Lingjun Li, Xudong Zhao, Tong Yu, Chao Wang, Yue Wang, Fei Wang, Weixu Qiao, Houbo He, Zeru Zhang, Zeyu Sun, Junxiong Mao, Chong Shen

Yuan 2. 0-M32, with a similar base architecture as Yuan-2. 0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active.


PatchScaler: An Efficient Patch-Independent Diffusion Model for Super-Resolution

1 code implementation27 May 2024 Yong liu, Hang Dong, Jinshan Pan, Qingji Dong, Kai Chen, Rongxiang Zhang, Lean Fu, Fei Wang

Diffusion models significantly improve the quality of super-resolved images with their impressive content generation capabilities.

Denoising Image Super-Resolution

Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models

no code implementations26 May 2024 Jiankun Wang, Sumyeong Ahn, Taykhoom Dalal, Xiaodan Zhang, Weishen Pan, Qiannan Zhang, Bin Chen, Hiroko H. Dodge, Fei Wang, Jiayu Zhou

Specifically, we develop a collaborative pipeline that combines SLs and LLMs via a confidence-driven decision-making mechanism, leveraging the strengths of SLs in clear-cut cases and LLMs in more complex scenarios.

Decision Making

GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing

1 code implementation18 May 2024 Chengqing Yu, Fei Wang, Zezhi Shao, Tangwen Qian, Zhao Zhang, Wei Wei, Yongjun Xu

In GinAR, it consists of two key components, that is, interpolation attention and adaptive graph convolution to take place of the fully connected layer of simple recursive units, and thus are capable of recovering all missing variables and reconstructing the correct spatial-temporal dependencies for recursively modeling of multivariate time series data, respectively.

Multivariate Time Series Forecasting Time Series

Joint Analysis of Single-Cell Data across Cohorts with Missing Modalities

1 code implementation18 May 2024 Marianne Arriola, Weishen Pan, Manqi Zhou, Qiannan Zhang, Chang Su, Fei Wang

Joint analysis of multi-omic single-cell data across cohorts has significantly enhanced the comprehensive analysis of cellular processes.


FA-Depth: Toward Fast and Accurate Self-supervised Monocular Depth Estimation

1 code implementation17 May 2024 Fei Wang, Jun Cheng

Most existing methods often rely on complex models to predict scene depth with high accuracy, resulting in slow inference that is not conducive to deployment.

Monocular Depth Estimation

Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G

no code implementations6 May 2024 Xiaoxue Yu, Xingfu Yi, Rongpeng Li, Fei Wang, Chenghui Peng, Zhifeng Zhao, Honggang Zhang

Existing distributed learning frameworks like Federated Learning and Split Learning often struggle with significant challenges in dynamic network environments including high synchronization demands, costly communication overheads, severe computing resource consumption, and data heterogeneity across network nodes.

Federated Learning Language Modelling +1

Cooperative Sentiment Agents for Multimodal Sentiment Analysis

1 code implementation19 Apr 2024 Shanmin Wang, Hui Shuai, Qingshan Liu, Fei Wang

In this paper, we propose a new Multimodal Representation Learning (MRL) method for Multimodal Sentiment Analysis (MSA), which facilitates the adaptive interaction between modalities through Cooperative Sentiment Agents, named Co-SA.

Disentanglement Multimodal Emotion Recognition +1

Offset Unlearning for Large Language Models

1 code implementation17 Apr 2024 James Y. Huang, Wenxuan Zhou, Fei Wang, Fred Morstatter, Sheng Zhang, Hoifung Poon, Muhao Chen

Despite the strong capabilities of Large Language Models (LLMs) to acquire knowledge from their training corpora, the memorization of sensitive information in the corpora such as copyrighted, harmful, and private content has led to ethical and legal concerns.


HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoising

no code implementations15 Apr 2024 Yang Liu, Jiahua Xiao, Yu Guo, Peilin Jiang, Haiwei Yang, Fei Wang

Effectively discerning spatial-spectral dependencies in HSI denoising is crucial, but prevailing methods using convolution or transformers still face computational efficiency limitations.

Computational Efficiency Denoising

Self-Improvement Programming for Temporal Knowledge Graph Question Answering

no code implementations2 Apr 2024 Zhuo Chen, Zhao Zhang, Zixuan Li, Fei Wang, Yutao Zeng, Xiaolong Jin, Yongjun Xu

Temporal Knowledge Graph Question Answering (TKGQA) aims to answer questions with temporal intent over Temporal Knowledge Graphs (TKGs).

Graph Question Answering In-Context Learning +3

FraGNNet: A Deep Probabilistic Model for Mass Spectrum Prediction

no code implementations2 Apr 2024 Adamo Young, Fei Wang, David Wishart, Bo wang, Hannes Röst, Russ Greiner

The process of identifying a compound from its mass spectrum is a critical step in the analysis of complex mixtures.


Monotonic Paraphrasing Improves Generalization of Language Model Prompting

no code implementations24 Mar 2024 Qin Liu, Fei Wang, Nan Xu, Tianyi Yan, Tao Meng, Muhao Chen

In this paper, we propose monotonic paraphrasing (MonoPara), an end-to-end decoding strategy that paraphrases given prompts or instructions into their lower perplexity counterparts based on an ensemble of a paraphrase LM for prompt (or instruction) rewriting, and a target LM (i. e. the prompt or instruction executor) that constrains the generation for lower perplexity.

Language Modelling

LocalMamba: Visual State Space Model with Windowed Selective Scan

1 code implementation14 Mar 2024 Tao Huang, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, Chang Xu

This paper posits that the key to enhancing Vision Mamba (ViM) lies in optimizing scan directions for sequence modeling.

Frequency Decoupling for Motion Magnification via Multi-Level Isomorphic Architecture

2 code implementations CVPR 2024 Fei Wang, Dan Guo, Kun Li, Zhun Zhong, Meng Wang

To this end, we present FD4MM, a new paradigm of Frequency Decoupling for Motion Magnification with a Multi-level Isomorphic Architecture to capture multi-level high-frequency details and a stable low-frequency structure (motion field) in video space.

Motion Magnification Representation Learning

A Dataset for the Validation of Truth Inference Algorithms Suitable for Online Deployment

1 code implementation10 Mar 2024 Fei Wang, Haoyu Liu, Haoyang Bi, Xiangzhuang Shen, Renyu Zhu, Runze Wu, Minmin Lin, Tangjie Lv, Changjie Fan, Qi Liu, Zhenya Huang, Enhong Chen

In this paper, we introduce a substantial crowdsourcing annotation dataset collected from a real-world crowdsourcing platform.

From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification

no code implementations10 Mar 2024 Fei Wang, Chao Shang, Sarthak Jain, Shuai Wang, Qiang Ning, Bonan Min, Vittorio Castelli, Yassine Benajiba, Dan Roth

We investigate common constraints in NLP tasks, categorize them into three classes based on the types of their arguments, and propose a unified framework, ACT (Aligning to ConsTraints), to automatically produce supervision signals for user alignment with constraints.

Abstractive Text Summarization Entity Typing +2

Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing

1 code implementation10 Mar 2024 Liyang He, Zhenya Huang, Jiayu Liu, Enhong Chen, Fei Wang, Jing Sha, Shijin Wang

In this paper, we propose an innovative Bit-mask Robust Contrastive knowledge Distillation (BRCD) method, specifically devised for the distillation of semantic hashing models.

Image Retrieval Knowledge Distillation +1

Unified Uncertainty Estimation for Cognitive Diagnosis Models

no code implementations9 Mar 2024 Fei Wang, Qi Liu, Enhong Chen, Chuanren Liu, Zhenya Huang, Jinze Wu, Shijin Wang

Specifically, based on the idea of estimating the posterior distributions of cognitive diagnosis model parameters, we first provide a unified objective function for mini-batch based optimization that can be more efficiently applied to a wide range of models and large datasets.

cognitive diagnosis

Automated Design and Optimization of Distributed Filtering Circuits via Reinforcement Learning

no code implementations22 Feb 2024 Peng Gao, Tao Yu, Fei Wang, Ru-Yue Yuan

Designing distributed filtering circuits (DFCs) is complex and time-consuming, with the circuit performance relying heavily on the expertise and experience of electronics engineers.

reinforcement-learning Reinforcement Learning (RL)

Vision-Language Navigation with Embodied Intelligence: A Survey

no code implementations22 Feb 2024 Peng Gao, Peng Wang, Feng Gao, Fei Wang, Ruyue Yuan

As a long-term vision in the field of artificial intelligence, the core goal of embodied intelligence is to improve the perception, understanding, and interaction capabilities of agents and the environment.

Vision-Language Navigation

MapTrack: Tracking in the Map

no code implementations20 Feb 2024 Fei Wang, Ruohui Zhang, Chenglin Chen, Min Yang, Yun Bai

The prediction map determines whether an object is in a crowd, and we prioritize state estimations over observations when severe deformation of observations occurs, accomplished through the covariance adaptive Kalman filter.

Multi-Object Tracking

Contrastive Instruction Tuning

1 code implementation17 Feb 2024 Tianyi Lorena Yan, Fei Wang, James Y. Huang, Wenxuan Zhou, Fan Yin, Aram Galstyan, Wenpeng Yin, Muhao Chen

Instruction tuning has been used as a promising approach to improve the performance of large language models (LLMs) on unseen tasks.


Privacy-Preserving Language Model Inference with Instance Obfuscation

no code implementations13 Feb 2024 Yixiang Yao, Fei Wang, Srivatsan Ravi, Muhao Chen

Language Models as a Service (LMaaS) offers convenient access for developers and researchers to perform inference using pre-trained language models.

Benchmarking Language Modelling +2

Instructional Fingerprinting of Large Language Models

1 code implementation21 Jan 2024 Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen

The exorbitant cost of training Large language models (LLMs) from scratch makes it essential to fingerprint the models to protect intellectual property via ownership authentication and to ensure downstream users and developers comply with their license terms (e. g. restricting commercial use).

Person-in-WiFi 3D: End-to-End Multi-Person 3D Pose Estimation with Wi-Fi

no code implementations CVPR 2024 Kangwei Yan, Fei Wang, Bo Qian, Han Ding, Jinsong Han, Xing Wei

This paper takes a step forward by introducing Person-in-WiFi 3D a pioneering Wi-Fi system that accomplishes multi-person 3D pose estimation.

3D Pose Estimation

Rethinking Tabular Data Understanding with Large Language Models

1 code implementation27 Dec 2023 Tianyang Liu, Fei Wang, Muhao Chen

Large Language Models (LLMs) have shown to be capable of various tasks, yet their capability in interpreting and reasoning over tabular data remains an underexplored area.

Semantic Parsing

Conversational Question Answering with Reformulations over Knowledge Graph

no code implementations27 Dec 2023 Lihui Liu, Blaine Hill, Boxin Du, Fei Wang, Hanghang Tong

CornNet adopts a teacher-student architecture where a teacher model learns question representations using human writing reformulations, and a student model to mimic the teacher model's output via reformulations generated by LLMs.

Conversational Question Answering Knowledge Graphs +1

AdapTraj: A Multi-Source Domain Generalization Framework for Multi-Agent Trajectory Prediction

no code implementations22 Dec 2023 Tangwen Qian, Yile Chen, Gao Cong, Yongjun Xu, Fei Wang

However, the development of multi-source domain generalization in this task presents two notable issues: (1) negative transfer; (2) inadequate modeling for external factors.

Domain Generalization Trajectory Prediction

EulerMormer: Robust Eulerian Motion Magnification via Dynamic Filtering within Transformer

1 code implementation7 Dec 2023 Fei Wang, Dan Guo, Kun Li, Meng Wang

Then, we introduce a novel dynamic filter that eliminates noise cues and preserves critical features in the motion magnification and amplification generation phases.

Denoising Motion Magnification

Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness

no code implementations19 Nov 2023 Gongbo Zhang, Qiao Jin, Denis Jered McInerney, Yong Chen, Fei Wang, Curtis L. Cole, Qian Yang, Yanshan Wang, Bradley A. Malin, Mor Peleg, Byron C. Wallace, Zhiyong Lu, Chunhua Weng, Yifan Peng

Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence.

Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking

no code implementations16 Nov 2023 Nan Xu, Fei Wang, Ben Zhou, Bang Zheng Li, Chaowei Xiao, Muhao Chen

While large language models (LLMs) have demonstrated increasing power, they have also given rise to a wide range of harmful behaviors.

Deceptive Semantic Shortcuts on Reasoning Chains: How Far Can Models Go without Hallucination?

1 code implementation16 Nov 2023 Bangzheng Li, Ben Zhou, Fei Wang, Xingyu Fu, Dan Roth, Muhao Chen

During the construction of the evidence, we purposefully replace semantic clues (entities) that may lead to the correct answer with distractor clues (evidence) that will not directly lead to the correct answer but require a chain-like reasoning process.

Hallucination Sentence

Towards Long-term Annotators: A Supervised Label Aggregation Baseline

no code implementations15 Nov 2023 Haoyu Liu, Fei Wang, Minmin Lin, Runze Wu, Renyu Zhu, Shiwei Zhao, Kai Wang, Tangjie Lv, Changjie Fan

These annotators could leave substantial historical annotation records on the crowdsourcing platforms, which can benefit label aggregation, but are ignored by previous works.

Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs

1 code implementation25 Oct 2023 Jacqueline Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang

Causal discovery is crucial for causal inference in observational studies, as it can enable the identification of valid adjustment sets (VAS) for unbiased effect estimation.

Causal Discovery Causal Inference +1

Marginal Nodes Matter: Towards Structure Fairness in Graphs

no code implementations23 Oct 2023 Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou

Specifically, we first analyzed multiple graphs and observed that marginal nodes in graphs have a worse performance of downstream tasks than others in graph neural networks.


Exploring the relationship between response time sequence in scale answering process and severity of insomnia: a machine learning approach

no code implementations13 Oct 2023 Zhao Su, Rongxun Liu, Keyin Zhou, Xinru Wei, Ning Wang, Zexin Lin, Yuanchen Xie, Jie Wang, Fei Wang, Shenzhong Zhang, Xizhe Zhang

The relationship between symptom severity and response time was explored, and a machine learning model was developed to predict the presence of insomnia.

SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction

1 code implementation10 Oct 2023 Fei Wang, Kongzhang Tang, Hefeng Wu, Baoquan Zhao, Hao Cai, Teng Zhou

Compared with natural images, freehand sketches are much more flexible to depict various shapes, providing a high potential and valuable way for 3D human reconstruction.

3D Human Reconstruction 3D Reconstruction +1

Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis

3 code implementations9 Oct 2023 Zezhi Shao, Fei Wang, Yongjun Xu, Wei Wei, Chengqing Yu, Zhao Zhang, Di Yao, Guangyin Jin, Xin Cao, Gao Cong, Christian S. Jensen, Xueqi Cheng

Moreover, based on the proposed BasicTS and rich heterogeneous MTS datasets, we conduct an exhaustive and reproducible performance and efficiency comparison of popular models, providing insights for researchers in selecting and designing MTS forecasting models.

Benchmarking Multivariate Time Series Forecasting +1

Coordination Control of Discrete Event Systems under Cyber Attacks

no code implementations21 Sep 2023 Fei Wang, Jan Komenda, Feng Lin

This paper investigates the coordination control of discrete event systems in the presence of combined sensor and actuator attacks.

Self-Augmentation Improves Zero-Shot Cross-Lingual Transfer

no code implementations19 Sep 2023 Fei Wang, Kuan-Hao Huang, Kai-Wei Chang, Muhao Chen

In this paper, we propose a simple yet effective method, SALT, to improve the zero-shot cross-lingual transfer of the multilingual pretrained language models without the help of such external data.

Multilingual NLP Zero-Shot Cross-Lingual Transfer

Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm

1 code implementation1 Sep 2023 Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su

However, we notice that this paradigm leads to the inevitable non-identifiability and explainability overfitting problem, which is harmful to the quantification of learners' cognitive states and the quality of web learning services.

cognitive diagnosis Decoder

Ensuring User-side Fairness in Dynamic Recommender Systems

no code implementations29 Aug 2023 Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong

In the ever-evolving landscape of user-item interactions, continual adaptation to newly collected data is crucial for recommender systems to stay aligned with the latest user preferences.

Fairness Recommendation Systems +1

Attention-Based Acoustic Feature Fusion Network for Depression Detection

1 code implementation24 Aug 2023 Xiao Xu, Yang Wang, Xinru Wei, Fei Wang, Xizhe Zhang

To rectify this, we present the novel Attention-Based Acoustic Feature Fusion Network (ABAFnet) for depression detection.

Depression Detection

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

1 code implementation24 Aug 2023 Fei Wang, Liang Ding, Jun Rao, Ye Liu, Li Shen, Changxing Ding

The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic.

Attribute Negation +1

CoNe: Contrast Your Neighbours for Supervised Image Classification

1 code implementation21 Aug 2023 Mingkai Zheng, Shan You, Lang Huang, Xiu Su, Fei Wang, Chen Qian, Xiaogang Wang, Chang Xu

Moreover, to further boost the performance, we propose ``distributional consistency" as a more informative regularization to enable similar instances to have a similar probability distribution.

Classification Image Classification

DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction

no code implementations7 Aug 2023 Chengqing Yu, Fei Wang, Zezhi Shao, Tao Sun, Lin Wu, Yongjun Xu

Multivariate time series long-term prediction, which aims to predict the change of data in a long time, can provide references for decision-making.

Decision Making Decoder +1

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

1 code implementation5 Aug 2023 Yong liu, Hang Dong, Boyang Liang, Songwei Liu, Qingji Dong, Kai Chen, Fangmin Chen, Lean Fu, Fei Wang

Since the high resolution of intermediate features in SISR models increases memory and computational requirements, efficient SISR transformers are more favored.

Image Super-Resolution

HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting

no code implementations27 Jul 2023 Zezhi Shao, Fei Wang, Zhao Zhang, Yuchen Fang, Guangyin Jin, Yongjun Xu

Then, we propose a novel Hierarchical U-net TransFormer (HUTFormer) to address the issues of long-term traffic forecasting.

Decoder Time Series +1

Bipartite Ranking Fairness through a Model Agnostic Ordering Adjustment

1 code implementation27 Jul 2023 Sen Cui, Weishen Pan, ChangShui Zhang, Fei Wang

xOrder consistently achieves a better balance between the algorithm utility and ranking fairness on a variety of datasets with different metrics.


Watch out Venomous Snake Species: A Solution to SnakeCLEF2023

1 code implementation19 Jul 2023 Feiran Hu, Peng Wang, Yangyang Li, Chenlong Duan, Zijian Zhu, Fei Wang, Faen Zhang, Yong Li, Xiu-Shen Wei

The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata.

Data Augmentation

A scoping review on multimodal deep learning in biomedical images and texts

no code implementations14 Jul 2023 Zhaoyi Sun, Mingquan Lin, Qingqing Zhu, Qianqian Xie, Fei Wang, Zhiyong Lu, Yifan Peng

In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research.

Cross-Modal Retrieval Decision Making +5

An empirical study of using radiology reports and images to improve ICU mortality prediction

no code implementations20 Jun 2023 Mingquan Lin, Song Wang, Ying Ding, Lihui Zhao, Fei Wang, Yifan Peng

Background: The predictive Intensive Care Unit (ICU) scoring system plays an important role in ICU management because it predicts important outcomes, especially mortality.

ICU Mortality Management +1

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models

no code implementations14 Jun 2023 Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov

While diffusion models excel at generating high-quality samples, their latent variables typically lack semantic meaning and are not suitable for representation learning.

Representation Learning

RHFedMTL: Resource-Aware Hierarchical Federated Multi-Task Learning

no code implementations1 Jun 2023 Xingfu Yi, Rongpeng Li, Chenghui Peng, Fei Wang, Jianjun Wu, Zhifeng Zhao

The rapid development of artificial intelligence (AI) over massive applications including Internet-of-things on cellular network raises the concern of technical challenges such as privacy, heterogeneity and resource efficiency.

Federated Learning Multi-Task Learning

HQDec: Self-Supervised Monocular Depth Estimation Based on a High-Quality Decoder

1 code implementation30 May 2023 Fei Wang, Jun Cheng

To this end, we propose a high-quality decoder (HQDec), with which multilevel near-lossless fine-grained information, obtained by the proposed adaptive axial-normalized position-embedded channel attention sampling module (AdaAxialNPCAS), can be adaptively incorporated into a low-resolution feature map with high-level semantics utilizing the proposed adaptive information exchange scheme.

Decoder Monocular Depth Estimation

Robust Natural Language Understanding with Residual Attention Debiasing

1 code implementation28 May 2023 Fei Wang, James Y. Huang, Tianyi Yan, Wenxuan Zhou, Muhao Chen

However, previous ensemble-based debiasing methods typically apply debiasing on top-level logits without directly addressing biased attention patterns.

Natural Language Understanding

Knowledge Diffusion for Distillation

1 code implementation NeurIPS 2023 Tao Huang, Yuan Zhang, Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Chang Xu

To address this, we propose to denoise student features using a diffusion model trained by teacher features.

Denoising Image Classification +4

From Shortcuts to Triggers: Backdoor Defense with Denoised PoE

1 code implementation24 May 2023 Qin Liu, Fei Wang, Chaowei Xiao, Muhao Chen

Language models are often at risk of diverse backdoor attacks, especially data poisoning.

backdoor defense Data Poisoning +3

Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality

1 code implementation24 May 2023 Tanay Dixit, Fei Wang, Muhao Chen

However, most of the prior works on training factuality-aware models have ignored the negative effect it has on summary quality.

Abstractive Text Summarization Contrastive Learning

A Causal View of Entity Bias in (Large) Language Models

1 code implementation24 May 2023 Fei Wang, Wenjie Mo, Yiwei Wang, Wenxuan Zhou, Muhao Chen

Building upon this SCM, we propose causal intervention techniques to mitigate entity bias for both white-box and black-box settings.

Machine Reading Comprehension Memorization +1

Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models

no code implementations24 May 2023 Jiashu Xu, Mingyu Derek Ma, Fei Wang, Chaowei Xiao, Muhao Chen

We investigate security concerns of the emergent instruction tuning paradigm, that models are trained on crowdsourced datasets with task instructions to achieve superior performance.

Continual Learning Data Poisoning

How Fragile is Relation Extraction under Entity Replacements?

1 code implementation22 May 2023 Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen

In principle, textual context determines the ground-truth relation and the RE models should be able to correctly identify the relations reflected by the textual context.

Benchmarking Causal Inference +2

Locate and Beamform: Two-dimensional Locating All-neural Beamformer for Multi-channel Speech Separation

no code implementations18 May 2023 Yanjie Fu, Meng Ge, Honglong Wang, Nan Li, Haoran Yin, Longbiao Wang, Gaoyan Zhang, Jianwu Dang, Chengyun Deng, Fei Wang

Recently, stunning improvements on multi-channel speech separation have been achieved by neural beamformers when direction information is available.

Speech Separation

Automated Data Denoising for Recommendation

no code implementations11 May 2023 Yingqiang Ge, Mostafa Rahmani, Athirai Irissappane, Jose Sepulveda, James Caverlee, Fei Wang

In real-world scenarios, most platforms collect both large-scale, naturally noisy implicit feedback and small-scale yet highly relevant explicit feedback.

Denoising Recommendation Systems

Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources

no code implementations10 May 2023 Suraj Rajendran, Weishen Pan, Mert R. Sabuncu, Yong Chen, Jiayu Zhou, Fei Wang

By offering a more comprehensive approach to healthcare data integration, patchwork learning has the potential to revolutionize the clinical applicability of ML models.

Data Integration

Towards clinical AI fairness: A translational perspective

no code implementations26 Apr 2023 Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu

In this paper, we discuss the misalignment between technical and clinical perspectives of AI fairness, highlight the barriers to AI fairness' translation to healthcare, advocate multidisciplinary collaboration to bridge the knowledge gap, and provide possible solutions to address the clinical concerns pertaining to AI fairness.

Fairness Translation

Can GPT-4 Perform Neural Architecture Search?

1 code implementation21 Apr 2023 Mingkai Zheng, Xiu Su, Shan You, Fei Wang, Chen Qian, Chang Xu, Samuel Albanie

We investigate the potential of GPT-4~\cite{gpt4} to perform Neural Architecture Search (NAS) -- the task of designing effective neural architectures.

Navigate Neural Architecture Search

Context-aware Domain Adaptation for Time Series Anomaly Detection

no code implementations15 Apr 2023 Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu

We formulate context sampling into the Markov decision process and exploit deep reinforcement learning to optimize the time series domain adaptation process via context sampling and design a tailored reward function to generate domain-invariant features that better align two domains for anomaly detection.

Anomaly Detection Diversity +4

Crowd Counting with Sparse Annotation

no code implementations12 Apr 2023 Shiwei Zhang, Zhengzheng Wang, Qing Liu, Fei Wang, Wei Ke, Tong Zhang

This paper presents a new annotation method called Sparse Annotation (SA) for crowd counting, which reduces human labeling efforts by sparsely labeling individuals in an image.

Crowd Counting

Neural Multi-network Diffusion towards Social Recommendation

no code implementations11 Apr 2023 Boxin Du, Lihui Liu, Jiejun Xu, Fei Wang, Hanghang Tong

Graph Neural Networks (GNNs) have been widely applied on a variety of real-world applications, such as social recommendation.

FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization

no code implementations15 Mar 2023 Qianqian Xie, Jiayu Zhou, Yifan Peng, Fei Wang

We propose to extract medical facts of the input medical report, its gold summary, and candidate summaries based on the RadGraph schema and design the fact-guided reranker to efficiently incorporate the extracted medical facts for selecting the optimal summary.

Graph Generation

FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning

1 code implementation11 Mar 2023 Zheqi Zhu, Yuchen Shi, Jiajun Luo, Fei Wang, Chenghui Peng, Pingyi Fan, Khaled B. Letaief

By adopting layer-wise pruning in local training and federated updating, we formulate an explicit FL pruning framework, FedLP (Federated Layer-wise Pruning), which is model-agnostic and universal for different types of deep learning models.

Federated Learning

NetMoST: A network-based machine learning approach for subtyping schizophrenia using polygenic SNP allele biomarkers

no code implementations31 Jan 2023 Xinru Wei, Shuai Dong, Zhao Su, Lili Tang, Pengfei Zhao, Chunyu Pan, Fei Wang, Yanqing Tang, Weixiong Zhang, Xizhe Zhang

Subtyping neuropsychiatric disorders like schizophrenia is essential for improving the diagnosis and treatment of complex diseases.

Towards NeuroAI: Introducing Neuronal Diversity into Artificial Neural Networks

no code implementations23 Jan 2023 Feng-Lei Fan, Yingxin Li, Hanchuan Peng, Tieyong Zeng, Fei Wang

In the human brain, neuronal diversity is an enabling factor for all kinds of biological intelligent behaviors.


CbwLoss: Constrained Bidirectional Weighted Loss for Self-supervised Learning of Depth and Pose

no code implementations12 Dec 2022 Fei Wang, Jun Cheng, Penglei Liu

Photometric differences are widely used as supervision signals to train neural networks for estimating depth and camera pose from unlabeled monocular videos.

Model Optimization Self-Supervised Learning

Denoising Self-attentive Sequential Recommendation

no code implementations8 Dec 2022 Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang

Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.

Denoising Sequential Recommendation

SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation

2 code implementations CVPR 2023 Wenxuan Zhang, Xiaodong Cun, Xuan Wang, Yong Zhang, Xi Shen, Yu Guo, Ying Shan, Fei Wang

We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.

Image Animation Talking Head Generation

Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields

no code implementations CVPR 2023 Yue Chen, Xingyu Chen, Xuan Wang, Qi Zhang, Yu Guo, Ying Shan, Fei Wang

Neural Radiance Fields (NeRF) have achieved photorealistic novel views synthesis; however, the requirement of accurate camera poses limits its application.

Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues

no code implementations10 Nov 2022 Canyu Chen, Haoran Wang, Matthew Shapiro, Yunyu Xiao, Fei Wang, Kai Shu

Because of the uniqueness and importance of combating health misinformation in social media, we conduct this survey to further facilitate interdisciplinary research on this problem.


AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease

no code implementations7 Nov 2022 Chengsheng Mao, Jie Xu, Luke Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer Pacheco, Borna Bonakdarpour, Robert Vassar, Guoqian Jiang, Fei Wang, Jyotishman Pathak, Yuan Luo

Materials and Methods: We identified 3657 patients diagnosed with MCI together with their progress notes from Northwestern Medicine Enterprise Data Warehouse (NMEDW) between 2000-2020.

Salience Allocation as Guidance for Abstractive Summarization

1 code implementation22 Oct 2022 Fei Wang, Kaiqiang Song, Hongming Zhang, Lifeng Jin, Sangwoo Cho, Wenlin Yao, Xiaoyang Wang, Muhao Chen, Dong Yu

Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance.

Abstractive Text Summarization

Application of Deep Learning on Single-Cell RNA-sequencing Data Analysis: A Review

no code implementations11 Oct 2022 Matthew Brendel, Chang Su, Zilong Bai, Hao Zhang, Olivier Elemento, Fei Wang

Single-cell RNA-sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously.

Cross-Modality Domain Adaptation for Freespace Detection: A Simple yet Effective Baseline

no code implementations6 Oct 2022 Yuanbin Wang, Leyan Zhu, Shaofei Huang, Tianrui Hui, Xiaojie Li, Fei Wang, Si Liu

To better bridge the domain gap between source domain (synthetic data) and target domain (real-world data), we also propose a Selective Feature Alignment (SFA) module which only aligns the features of consistent foreground area between the two domains, thus realizing inter-domain intra-modality adaptation.

Autonomous Driving Semantic Segmentation +1

A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface

no code implementations7 Sep 2022 Jingcong Li, Fei Wang, Haiyun Huang, Feifei Qi, JiaHui Pan

The proposed SSML learns a meta model with the existing subjects first, then fine-tunes the model in a semi-supervised learning manner, i. e. using few labeled and many unlabeled samples of target subject for calibration.

Brain Computer Interface Emotion Recognition +4

Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting

1 code implementation10 Aug 2022 Zezhi Shao, Zhao Zhang, Fei Wang, Wei Wei, Yongjun Xu

These results suggest that we can design efficient and effective models as long as they solve the indistinguishability of samples, without being limited to STGNNs.

Multivariate Time Series Forecasting Time Series

Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization

1 code implementation18 Jul 2022 Yuhao Huang, Hang Dong, Jinshan Pan, Chao Zhu, Yu Guo, Ding Liu, Lean Fu, Fei Wang

We develop two simple yet effective plug and play methods to improve the performance of existing local and non-local propagation-based VSR algorithms on widely-used public videos.

Video Super-Resolution

ScaleNet: Searching for the Model to Scale

1 code implementation15 Jul 2022 Jiyang Xie, Xiu Su, Shan You, Zhanyu Ma, Fei Wang, Chen Qian

Recently, community has paid increasing attention on model scaling and contributed to developing a model family with a wide spectrum of scales.

HEAD: HEtero-Assists Distillation for Heterogeneous Object Detectors

1 code implementation12 Jul 2022 Luting Wang, Xiaojie Li, Yue Liao, Zeren Jiang, Jianlong Wu, Fei Wang, Chen Qian, Si Liu

We observe that the core difficulty for heterogeneous KD (hetero-KD) is the significant semantic gap between the backbone features of heterogeneous detectors due to the different optimization manners.

Knowledge Distillation Object +3

Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets

no code implementations12 Jul 2022 Yingsong Huang, Bing Bai, Shengwei Zhao, Kun Bai, Fei Wang

The second issue refers to that models may output misleading predictions due to epistemic uncertainty and aleatoric uncertainty, thus existing methods that rely solely on the output probabilities may fail to distinguish confident samples.

LightViT: Towards Light-Weight Convolution-Free Vision Transformers

1 code implementation12 Jul 2022 Tao Huang, Lang Huang, Shan You, Fei Wang, Chen Qian, Chang Xu

Vision transformers (ViTs) are usually considered to be less light-weight than convolutional neural networks (CNNs) due to the lack of inductive bias.

Image Classification Inductive Bias +3

Geometric Matrix Completion via Sylvester Multi-Graph Neural Network

no code implementations19 Jun 2022 Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong

Despite the success of the Sylvester equation empowered methods on various graph mining applications, such as semi-supervised label learning and network alignment, there also exists several limitations.

Graph Mining Graph Neural Network +1

Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting

1 code implementation18 Jun 2022 Zezhi Shao, Zhao Zhang, Wei Wei, Fei Wang, Yongjun Xu, Xin Cao, Christian S. Jensen

However, intuitively, traffic data encompasses two different kinds of hidden time series signals, namely the diffusion signals and inherent signals.

Graph Learning Graph Neural Network +2

Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data

no code implementations18 Jun 2022 Jianmin Chen, Robert H. Aseltine, Fei Wang, Kun Chen

In a suicide risk study with EHR data, our approach is able to select and aggregate prior mental health diagnoses as guided by the diagnosis hierarchy of the International Classification of Diseases.

Dimensionality Reduction feature selection +1

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

2 code implementations18 Jun 2022 Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu

However, the patterns of time series and the dependencies between them (i. e., the temporal and spatial patterns) need to be analyzed based on long-term historical MTS data.

Ranked #2 on Traffic Prediction on PEMS-BAY (using extra training data)

Graph Neural Network Multivariate Time Series Forecasting +2

Response to: Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders. Molecular Psychiatry (2022)

no code implementations10 Jun 2022 Xizhe Zhang, Fei Wang, Weixiong Zhang

They questioned the generalizability of our methods and the statistical significance, stability, and overfitting of the results, and proposed a pipeline for disease subtyping.

BIG-bench Machine Learning Misconceptions

Masked Distillation with Receptive Tokens

1 code implementation29 May 2022 Tao Huang, Yuan Zhang, Shan You, Fei Wang, Chen Qian, Jian Cao, Chang Xu

To obtain a group of masks, the receptive tokens are learned via the regular task loss but with teacher fixed, and we also leverage a Dice loss to enrich the diversity of learned masks.

object-detection Object Detection +1

Green Hierarchical Vision Transformer for Masked Image Modeling

1 code implementation26 May 2022 Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Toshihiko Yamasaki

We present an efficient approach for Masked Image Modeling (MIM) with hierarchical Vision Transformers (ViTs), allowing the hierarchical ViTs to discard masked patches and operate only on the visible ones.

Object Detection

Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing

1 code implementation25 May 2022 Nan Xu, Fei Wang, Bangzheng Li, Mingtao Dong, Muhao Chen

Due to shortcuts from surface patterns to annotated entity labels and biased training, existing entity typing models are subject to the problem of spurious correlations.

counterfactual Data Augmentation +2

Knowledge Distillation from A Stronger Teacher

2 code implementations21 May 2022 Tao Huang, Shan You, Fei Wang, Chen Qian, Chang Xu

In this paper, we show that simply preserving the relations between the predictions of teacher and student would suffice, and propose a correlation-based loss to capture the intrinsic inter-class relations from the teacher explicitly.

Ranked #3 on Knowledge Distillation on ImageNet (using extra training data)

Image Classification Knowledge Distillation +2

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning

1 code implementation NAACL 2022 Fei Wang, Zhewei Xu, Pedro Szekely, Muhao Chen

This prunes the full self-attention structure into an order-invariant graph attention that captures the connected graph structure of cells belonging to the same row or column, and it differentiates between relevant cells and irrelevant cells from the structural perspective.

Data Augmentation Data-to-Text Generation +3

A Keypoint-based Global Association Network for Lane Detection

1 code implementation CVPR 2022 Jinsheng Wang, Yinchao Ma, Shaofei Huang, Tianrui Hui, Fei Wang, Chen Qian, Tianzhu Zhang

Earlier works follow a top-down roadmap to regress predefined anchors into various shapes of lane lines, which lacks enough flexibility to fit complex shapes of lanes due to the fixed anchor shapes.

Ranked #4 on Lane Detection on TuSimple (F1 score metric)

Keypoint Estimation Lane Detection

Multimodal Machine Learning in Precision Health

no code implementations10 Apr 2022 Adrienne Kline, Hanyin Wang, Yikuan Li, Saya Dennis, Meghan Hutch, Zhenxing Xu, Fei Wang, Feixiong Cheng, Yuan Luo

Attempts to improve prediction and resemble the multimodal nature of clinical expert decision-making this has been met in the computational field of machine learning by a fusion of disparate data.

BIG-bench Machine Learning Decision Making

BiSyn-GAT+: Bi-Syntax Aware Graph Attention Network for Aspect-based Sentiment Analysis

1 code implementation Findings (ACL) 2022 Shuo Liang, Wei Wei, Xian-Ling Mao, Fei Wang, Zhiyong He

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims to align aspects and corresponding sentiments for aspect-specific sentiment polarity inference.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2

TR-MOT: Multi-Object Tracking by Reference

no code implementations30 Mar 2022 Mingfei Chen, Yue Liao, Si Liu, Fei Wang, Jenq-Neng Hwang

RS takes previous detected results as references to aggregate the corresponding features from the combined features of the adjacent frames and makes a one-to-one track state prediction for each reference in parallel.

Multi-Object Tracking Object

Learning Where to Learn in Cross-View Self-Supervised Learning

1 code implementation CVPR 2022 Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Toshihiko Yamasaki

In this paper, we present a new approach, Learning Where to Learn (LEWEL), to adaptively aggregate spatial information of features, so that the projected embeddings could be exactly aligned and thus guide the feature learning better.

object-detection Object Detection +3

UV Volumes for Real-time Rendering of Editable Free-view Human Performance

1 code implementation CVPR 2023 Yue Chen, Xuan Wang, Xingyu Chen, Qi Zhang, Xiaoyu Li, Yu Guo, Jue Wang, Fei Wang

Neural volume rendering enables photo-realistic renderings of a human performer in free-view, a critical task in immersive VR/AR applications.

Searching for Network Width with Bilaterally Coupled Network

1 code implementation25 Mar 2022 Xiu Su, Shan You, Jiyang Xie, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu

In BCNet, each channel is fairly trained and responsible for the same amount of network widths, thus each network width can be evaluated more accurately.


DyRep: Bootstrapping Training with Dynamic Re-parameterization

2 code implementations CVPR 2022 Tao Huang, Shan You, Bohan Zhang, Yuxuan Du, Fei Wang, Chen Qian, Chang Xu

Structural re-parameterization (Rep) methods achieve noticeable improvements on simple VGG-style networks.

Weak Augmentation Guided Relational Self-Supervised Learning

no code implementations16 Mar 2022 Mingkai Zheng, Shan You, Fei Wang, Chen Qian, ChangShui Zhang, Xiaogang Wang, Chang Xu

Self-supervised Learning (SSL) including the mainstream contrastive learning has achieved great success in learning visual representations without data annotations.

Contrastive Learning Relation +2

Where Does the Performance Improvement Come From? -- A Reproducibility Concern about Image-Text Retrieval

1 code implementation8 Mar 2022 Jun Rao, Fei Wang, Liang Ding, Shuhan Qi, Yibing Zhan, Weifeng Liu, DaCheng Tao

In contrast to previous works, we focus on the reproducibility of the approaches and the examination of the elements that lead to improved performance by pretrained and nonpretrained models in retrieving images and text.

Image-text Retrieval Information Retrieval +1

CTformer: Convolution-free Token2Token Dilated Vision Transformer for Low-dose CT Denoising

2 code implementations28 Feb 2022 Dayang Wang, Fenglei Fan, Zhan Wu, Rui Liu, Fei Wang, Hengyong Yu

Furthermore, an overlapped inference mechanism is introduced to effectively eliminate the boundary artifacts that are common for encoder-decoder-based denoising models.

Decoder Denoising

Relational Surrogate Loss Learning

1 code implementation ICLR 2022 Tao Huang, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu

Evaluation metrics in machine learning are often hardly taken as loss functions, as they could be non-differentiable and non-decomposable, e. g., average precision and F1 score.

Image Classification Machine Reading Comprehension +3

Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets

1 code implementation AAAI 2022 Mengying Sun, Fei Wang, Olivier Elemento, Jiayu Zhou

In this work, we proposed a DDI detection method based on molecular structures using graph convolutional networks and deep sets.