Dongsoo Lee
17 papers · 2018–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Academic Marathon (7) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (12)
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(12)
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Renaissance Researcher
(5)
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(27)
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Dynamic Duo
(14)
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Triple Crown
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Topic Pioneer
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Keyword Collector
(53)
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Trend Setter
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Conference Pioneer
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Century Club
(17)
Conferences
ICLR (6)
NIPS (5)
EMNLP (2)
ACL (1)
CVPR (1)
ICML (1)
NAACL (1)
Top co-authors
Keywords
model compression
(7)
large language model
(4)
neural network optimization
(4)
weight quantization
(4)
parameter-efficient fine-tuning
(3)
binary quantization
(2)
post-training quantization
(2)
knowledge distillation
(1)
low-rank approximation
(1)
neural encoding
(1)
network pruning
(1)
maximum likelihood
(1)
fisher information
(1)
parameter sharing
(1)
population coding
(1)
information geometry
(1)
training efficiency
(1)
neural machine translation
(1)
generative model
(1)
parameter optimization
(1)
Papers
Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
ACL 2025
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices
NAACL 2025
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models
ICLR 2024
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
NIPS 2024
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
ICLR 2024
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
NIPS 2023
Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic
ICLR 2023
Information Geometry of the Retinal Representation Manifold
NIPS 2023
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
ICML 2023
AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models
EMNLP 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model
NIPS 2022
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression
ICLR 2022
FleXOR: Trainable Fractional Quantization
NIPS 2020
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation
EMNLP 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