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Computer Science 논문 리뷰
Computer Science 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
9999+개의 결과
Instruction Tuning for Large Language Models: A Survey
Shengyu Zhang, Linfeng Dong 외 9명
arXiv (Cornell University)
|
2023
|
96 회 인용
Large Language Models Struggle to Learn Long-Tail Knowledge
Nikhil Kandpal, Haikang Deng 외 3명
arXiv (Cornell University)
|
2022
|
96 회 인용
Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
Jian Sun, Wenfei Cao 외 2명
arXiv (Cornell University)
|
2015
|
96 회 인용
Learning Deep Transformer Models for Machine Translation
Qiang Wang, Bei Li 외 5명
arXiv (Cornell University)
|
2019
|
96 회 인용
Learning Representations for Automatic Colorization
Gustav Larsson, Michael Maire 외 1명
arXiv (Cornell University)
|
2016
|
96 회 인용
Learning to Learn: Meta-Critic Networks for Sample Efficient Learning
Flood Sung, Li Zhang 외 3명
arXiv (Cornell University)
|
2017
|
96 회 인용
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
Regina Barzilay, Lillian Lee
ArXiv.org
|
2003
|
96 회 인용
Maxwell Construction: The Hidden Bridge between Iterative and Maximum a Posteriori Decoding
Cyril Méasson, Andrea Montanari 외 1명
arXiv (Cornell University)
|
2005
|
96 회 인용
Meta-Gradient Reinforcement Learning
Zhongwen Xu, Hado van Hasselt 외 1명
arXiv (Cornell University)
|
2018
|
96 회 인용
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm
Chelsea Finn, Sergey Levine
arXiv (Cornell University)
|
2017
|
96 회 인용
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