Yiren Zhao
23 papers · 2019–2026 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(20)
Deep Learning
(17)
Artificial Intelligence
(12)
Application Areas
(11)
Architectures
(9)
Core AI
(8)
Optimization & Theory Β· Machine Learning
(6)
Optimization & Theory Β· Deep Learning
(6)
Learning Types Β· Machine Learning
(5)
Learning Types Β· Deep Learning
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Natural Language Processing
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Learning Paradigms
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Resources & Methods
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Techniques
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Computer Vision
(2)
Keywords
model compression
(7)
large language model
(4)
model quantization
(3)
transfer learning
(2)
federated learning
(2)
low-rank approximation
(2)
parameter-efficient fine-tuning
(2)
adversarial attack
(2)
memory efficiency
(2)
few-shot learning
(2)
adversarial machine learning
(2)
memory optimization
(2)
convolutional neural network
(2)
backdoor attack
(2)
low-rank adaptation
(2)
adversarial optimization
(1)
data poisoning
(1)
image classification
(1)
neural network security
(1)
image generation
(1)
Papers
Deep Kernel Fusion for Transformers
ACL 2026
Cached Multi-Lora Composition for Multi-Concept Image Generation
ICLR 2025
Hardware and Software Platform Inference
ICML 2025
Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization
EMNLP 2025
QERA: an Analytical Framework for Quantization Error Reconstruction
ICLR 2025
Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models
ACL 2025
Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences
NeurIPS 2024
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
NeurIPS 2024
LQER: Low-Rank Quantization Error Reconstruction for LLMs
ICML 2024
Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity
CVPR 2023
Architectural Backdoors in Neural Networks
CVPR 2023
Dynamic Stashing Quantization for Efficient Transformer Training
EMNLP 2023
MiliPoint: A Point Cloud Dataset for mmWave Radar
NeurIPS 2023
Revisiting Automated Prompting: Are We Actually Doing Better?
ACL 2023
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?
EMNLP 2023
Revisiting Structured Dropout
ACML 2023
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
ICML 2022
Rapid Model Architecture Adaption for Meta-Learning
NeurIPS 2022
Manipulating SGD with Data Ordering Attacks
NeurIPS 2021
Markpainting: Adversarial Machine Learning meets Inpainting
ICML 2021
Pay Attention to Features, Transfer Learn Faster CNNs
ICLR 2020
Dynamic Channel Pruning: Feature Boosting and Suppression
ICLR 2019
Focused Quantization for Sparse CNNs
NeurIPS 2019