paper review start

paper review

papers related to artificial intelligence and computer science will be reviewed.

• Title
  • blog post link
  • paper link

index

• Wang et al., BitNet: Scaling 1-bit Transformers for Large Language Models. 2023
  • https://minchocoin.github.io/paper-review/bitnet-scaling-1-bit-transformers-for-large-language-models-review/
  • https://arxiv.org/abs/2310.11453
• Howard et al., MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. 2017
  • https://minchocoin.github.io/paper-review/mobilenets-efficient-convolutional-neural-network-for-mobile-vision-applications/
  • https://arxiv.org/abs/1704.04861

Papers I have read but not posted

• Hu et al., mmPose-FK: A Forward Kinematics Approach to Dynamic Skeletal Pose Estimation Using mmWave Radars. 2024
  • https://ieeexplore.ieee.org/document/10382450
• Huynh et al., Ambient Backscatter: A Novel Method to Defend Jamming Attacks for Wireless Networks. 2019
  • https://ieeexplore.ieee.org/document/8869911
• Guo et al., Deep-Reinforcement-Learning-Based QoS-Aware Secure Routing for SDN-IoT. 2020
  • https://ieeexplore.ieee.org/document/8935210

Future reading and posting list

Large Language Models

• Luong et al., Effective Approaches to Attention-based Neural Machine Translation. 2015
  • https://arxiv.org/abs/1508.04025
• Vaswani et al., Attention Is All You Need. 2017
  • https://arxiv.org/abs/1706.03762
• Devlin et al., BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. 2018
  • https://arxiv.org/abs/1810.04805
• Radford et al., Improving Language Understanding by Generative Pre-Training
  • https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf
• Brown et al., Language Models are Few-Shot Learners. 2020
  • https://arxiv.org/abs/2005.14165
• Wei et al., Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. 2022
  • https://arxiv.org/abs/2201.11903
• Ouyang et al., Training language models to follow instructions with human feedback. 2022
  • https://arxiv.org/abs/2203.02155

AlphaGo

• Silver et al., Mastering the game of Go with deep neural networks and tree search. 2016
  • https://www.nature.com/articles/nature16961
• Silver et al., Mastering the game of Go without human knowledge. 2017
  • https://www.nature.com/articles/nature24270
• Silver et al., Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
  • https://arxiv.org/abs/1712.01815