/paper_annotations

A place to keep track of all the annotated papers.

MIT LicenseMIT

A place to keep track of all the annotated research papers. The aim of this repo is to house the annotated versions of trending/impactful research papers in machine learning. According to me the skill of reading research papers is very important for beginners and experienced folks alike. With a plethora of content out there in terms of blogs and jargon and complex terms(calling back to old papers, concepts, etc) the newer folks are simply moving away from it.

In order to make paper reading more accessible, I try to annotate, give insights, try to break some jargon on the paper itself, and carefully color-coding the highlights to distinguish the work already done vs the work proposed in the paper. This is my attempt to give back to the community in the tiniest of ways :D. Hope this is helpful to the people and helps in inculcating a habit of paper reading among all.

Papers

Paper Conference Year
1. PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks ICPR 2020
2. Attention is All you Need NeurIPS 2017
3. MLP-Mixer: An all MLP Architecture for Vision CVPR May 2021
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding NAACL 19 2018
5. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks ICML 2019
6. EfficientNetV2: Smaller Models and Faster Training ICML 2021
7. Few-Shot Named Entity Recognition: A Comprehensive Study Dec 2020
8. RoBERTa: A Robustly Optimized BERT Pretraining Approach Jul 2019
9. LayoutLM: Pre-training of Text and Layout for Document Image Understanding KDD 20 Dec 2019
10. Fastformer: Additive Attention Can Be All You Need Sep 2021
11. LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document Understanding ACL Sep 2021
12. WebFormer: The Web-page Transformer for Structure Information Extraction WWW Feb 2022
13. An Attention Free Transformer Sep 2021
14. DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMER Mar 2022

Sample Annotations

Color Scheme

Color Meaning
Green Topics about the current paper
Yellow Topics about other relevant references
Blue Implementation details/ maths/experiments
Red Text including my thoughts, questions, and understandings