steventan0110/Paper_Reading

Summary of my past readings on ML, CV, NLP-related paper. Currently, the update focuses on machine translation and general model architectures.

About Me

I am currently a graduate student at Johns Hopkins University. My research interests include Machine Translation, Image Processing, Model Interpretation & Robustness and Multi-Model Tasks

My Reading for Papers in ML, NLP, CV, and More.

Machine Learning (ML)

• Optimization
• Architecture (RNN, CNN, Transformer and More)
• Reinforcement Learning
• Generative Adversarial Network (GAN)
• Variational Autoencoders (VAE)
• Information Retrieval

Natural Language Processing (NLP)

• Language Modelling
• Word, Sentence, Document Embedding
• Debiasing in NLP
• Machine Translation
  • Adversarial Attack for NMT
  • Quality Estimation for NMT
  • Translation Memory in NMT
  • Structural Prediction for NMT
  • Denoise and Data Filtering
  • Low-Resource and Multilingual Translation
  • Bilingual Lexicon Induction
• Question Answering
• Text segmentation and labeling
• Text Generation
• Text Summarization
• Text Classification
• Neuro-Symbolic Hybrids

Computer Vision (CV)

• Image Classification and Segmentation
• Visual Question Answering
• Image Captioning