Yixing Xu
20 papers · 2017–2026 · 7 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (39) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
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Dynamic Duo
(12)
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Prolific Year · Productive
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Unstoppable · Bronze
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Century Club · Bronze
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Keyword Collector
(99)
Top co-authors
Research topics
Machine Learning
(18)
Deep Learning
(14)
Artificial Intelligence
(13)
Application Areas
(11)
Core AI · Artificial Intelligence
(11)
Optimization & Theory · Deep Learning
(10)
Optimization & Theory · Machine Learning
(8)
Architectures
(6)
Learning Types · Machine Learning
(6)
Core Methods
(3)
Learning Types · Deep Learning
(3)
Techniques
(3)
Computer Vision
(2)
Core AI · Computer Vision
(2)
Learning Paradigms
(2)
Keywords
model compression
(9)
vision transformer
(4)
positive-unlabeled learning
(3)
semi-supervised learning
(2)
neural architecture search
(2)
knowledge distillation
(2)
binary neural network
(2)
generalization bound
(2)
neural network binarization
(2)
performance prediction
(2)
neural network optimization
(2)
multi-class classification
(2)
filter pruning
(2)
source-free domain adaptation
(1)
feature selection
(1)
manifold regularization
(1)
contrastive learning
(1)
federated learning
(1)
domain adaptation
(1)
model aggregation
(1)
Papers
Learnable Permutation for Structured Sparsity on Transformer Models
AAAI 2026
SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning
AAAI 2026
Enhancing One-Shot Pruned Pre-trained Language Models through Sparse-Dense-Sparse Mechanism
COLING 2025
Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding
ICML 2025
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module
ICML 2024
QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
NeurIPS 2024
FDViT: Improve the Hierarchical Architecture of Vision Transformer
ICCV 2023
BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons
NeurIPS 2022
Federated Learning with Positive and Unlabeled Data
ICML 2022
Source-Free Domain Adaptation via Distribution Estimation
CVPR 2022
Learning Frequency Domain Approximation for Binary Neural Networks
NeurIPS 2021
Manifold Regularized Dynamic Network Pruning
CVPR 2021
ReNAS: Relativistic Evaluation of Neural Architecture Search
CVPR 2021
A Semi-Supervised Assessor of Neural Architectures
CVPR 2020
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks
AAAI 2020
Kernel Based Progressive Distillation for Adder Neural Networks
NeurIPS 2020
SCOP: Scientific Control for Reliable Neural Network Pruning
NeurIPS 2020
Training Binary Neural Networks through Learning with Noisy Supervision
ICML 2020
Positive-Unlabeled Compression on the Cloud
NeurIPS 2019
Multi-Positive and Unlabeled Learning
IJCAI 2017