Se Jung Kwon
16 papers · 2020–2025 · 7 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (28)
π±
Topic Pioneer
π
Triple Crown
π€
Dynamic Duo
(14)
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(69)
Top co-authors
Research topics
Deep Learning
(13)
Machine Learning
(13)
Application Areas
(11)
Artificial Intelligence
(10)
Core AI
(10)
Optimization & Theory Β· Machine Learning
(6)
Optimization & Theory Β· Deep Learning
(6)
Models
(5)
Natural Language Processing
(4)
Learning Types Β· Machine Learning
(3)
Resources & Methods
(3)
Architectures
(2)
Learning Types Β· Deep Learning
(2)
Techniques
(2)
Computer Vision
(1)
Keywords
model compression
(9)
weight quantization
(6)
neural network optimization
(4)
large language model
(4)
parameter-efficient fine-tuning
(3)
generative model
(3)
model quantization
(2)
post-training quantization
(2)
image generation
(2)
score-based model
(2)
diffusion model
(2)
matrix multiplication
(2)
binary quantization
(2)
parameter sharing
(1)
label noise
(1)
neural machine translation
(1)
maximum likelihood
(1)
low-rank approximation
(1)
in-context learning
(1)
energy efficiency
(1)
Papers
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices
NAACL 2025
Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
ACL 2025
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
NeurIPS 2024
Label-Noise Robust Diffusion Models
ICLR 2024
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
ICLR 2024
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models
ICLR 2024
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
ICML 2023
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
NeurIPS 2023
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
ICML 2023
Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic
ICLR 2023
AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models
EMNLP 2022
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression
ICLR 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model
NeurIPS 2022
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation
EMNLP 2020
FleXOR: Trainable Fractional Quantization
NeurIPS 2020
Structured Compression by Weight Encryption for Unstructured Pruning and Quantization
CVPR 2020