Peisong Wang
28 papers · 2017–2026 · 10 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (45) π Academic Marathon Β· Sprint π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Dynamic Duo
(23)
π§
Keyword Pioneer
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Deep Specialist
(13)
π
Renaissance Researcher
(7)
π₯
Unstoppable Β· Silver
β‘
Prolific Year Β· Productive
π
Conference Pioneer
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Century Club Β· Bronze
ποΈ
Keyword Collector
(109)
Venues
Top co-authors
Research topics
Machine Learning
(21)
Deep Learning
(20)
Application Areas
(17)
Artificial Intelligence
(12)
Core AI
(11)
Optimization & Theory Β· Deep Learning
(10)
Architectures
(9)
Optimization & Theory Β· Machine Learning
(8)
Models
(5)
Techniques
(5)
Computer Vision
(4)
Core Methods
(3)
Learning Types
(3)
Processing
(3)
Generation
(2)
Keywords
model compression
(10)
efficient computing
(6)
large language model
(6)
model quantization
(4)
post-training quantization
(4)
neural network quantization
(3)
neural network optimization
(2)
network quantization
(2)
weight quantization
(2)
graph neural network
(2)
graph representation
(2)
efficient inference
(2)
memory efficiency
(2)
differential privacy
(2)
neural network
(2)
attention mechanism
(2)
transfer learning
(1)
network architecture
(1)
image generation
(1)
vision transformer
(1)
Papers
A Universal Self-Attention Enhancement for Bridging Low-bit Quantization and Vision Transformers
WACV 2026
MemeBQ:Memory Efficient Binary Quantization of LLMs
AAAI 2026
SparVAR: Exploring Sparsity in Visual AutoRegressive Modeling for Training-Free Acceleration
CVPR 2026
EAC-MoE: Expert-Selection Aware Compressor for Mixture-of-Experts Large Language Models
ACL 2025
FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
ICML 2025
LoRaDA: Low-Rank Direct Attention Adaptation for Efficient LLM Fine-tuning
EMNLP 2025
Q-Mamba: Towards more efficient Mamba models via post-training quantization
ACL 2025
RQT: Hierarchical Residual Quantization for Multi-Model Compression
ACL 2025
S2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning
ACL 2025
A Survey of Graph Meets Large Language Model: Progress and Future Directions
IJCAI 2024
GLBench: A Comprehensive Benchmark for Graph with Large Language Models
NeurIPS 2024
Patch-Aware Sample Selection for Efficient Masked Image Modeling
AAAI 2024
Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration
ICML 2024
Towards Efficient and Accurate Winograd Convolution via Full Quantization
NeurIPS 2023
Differentially Private Federated Learning With Local Regularization and Sparsification
CVPR 2022
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy
AAAI 2022
Towards Fully Sparse Training: Information Restoration with Spatial Similarity
AAAI 2022
Towards Mixed-Precision Quantization of Neural Networks via Constrained Optimization
ICCV 2021
ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices
ECCV 2020
Soft Threshold Ternary Networks
IJCAI 2020
Sparsity-Inducing Binarized Neural Networks
AAAI 2020
Towards Accurate Post-training Network Quantization via Bit-Split and Stitching
ICML 2020
K-Nearest Neighbors Hashing
CVPR 2019
ODE-Inspired Network Design for Single Image Super-Resolution
CVPR 2019
Reading selectively via Binary Input Gated Recurrent Unit
IJCAI 2019
Training Binary Weight Networks via Semi-Binary Decomposition
ECCV 2018
Two-Step Quantization for Low-Bit Neural Networks
CVPR 2018
Fixed-Point Factorized Networks
CVPR 2017