Dongsoo Lee
17 papers · 2018–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (28) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Topic Pioneer
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Triple Crown
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Deep Specialist
(10)
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Keyword Champion
(7)
π€
Dynamic Duo
(14)
ποΈ
Keyword Collector
(72)
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Conference Pioneer
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(15)
Artificial Intelligence
(12)
Deep Learning
(12)
Application Areas
(12)
Core AI
(12)
Optimization & Theory Β· Machine Learning
(8)
Optimization & Theory Β· Deep Learning
(6)
Natural Language Processing
(4)
Models
(3)
Resources & Methods
(3)
Techniques
(3)
Architectures
(2)
Core Methods
(2)
Learning Types
(2)
Interdisciplinary
(1)
Keywords
model compression
(11)
weight quantization
(7)
large language model
(4)
neural network optimization
(4)
parameter-efficient fine-tuning
(3)
weight pruning
(3)
post-training quantization
(2)
model quantization
(2)
binary quantization
(2)
matrix multiplication
(2)
neural network
(2)
sparse matrix
(2)
fisher information
(1)
maximum likelihood
(1)
knowledge distillation
(1)
low-rank approximation
(1)
energy efficiency
(1)
neural encoding
(1)
network pruning
(1)
parameter optimization
(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
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
Information Geometry of the Retinal Representation Manifold
NeurIPS 2023
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
NeurIPS 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
Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network
ICLR 2019
Viterbi-based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio
ICLR 2018