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.

• 📫 How to reach me @akshayuppal12
• 📄 Know about my experiences on LinkedIn
• Check out my blog for such papers, tutorials and more: https://au1206.github.io/

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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

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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

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