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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

PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022

Sample Annotations

Color Scheme

ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings

About

A place to keep track of all the annotated papers.

au1206.github.io/

Topics

annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning

Resources

Readme
MIT license

Code of conduct

Code of conduct

Contributing

Contributing
Activity

Stars

177 stars

Watchers

5 watching

Forks

19 forks
Report repository

Releases

Packages

Contributors

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
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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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
About
A place to keep track of all the annotated papers.
au1206.github.io/
Topics
annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
177 stars
Watchers
5 watching
Forks
19 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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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
PaperConferenceYear
1.PICK : Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional NetworksICPR2020
2.Attention is All you NeedNeurIPS2017
3.MLP-Mixer: An all MLP Architecture for VisionCVPRMay 2021
4.BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingNAACL 192018
5.EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksICML2019
6.EfficientNetV2: Smaller Models and Faster TrainingICML2021
7.Few-Shot Named Entity Recognition: A Comprehensive StudyDec 2020
8.RoBERTa: A Robustly Optimized BERT Pretraining ApproachJul 2019
9.LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingKDD 20Dec 2019
10.Fastformer: Additive Attention Can Be All You NeedSep 2021
11.LayoutLMv2: Multi-Modal Pre-Training For Visually-Rich Document UnderstandingACLSep 2021
12.WebFormer: The Web-page Transformer for Structure Information ExtractionWWWFeb 2022
13.An Attention Free TransformerSep 2021
14.DIT: SELF-SUPERVISED PRE-TRAINING FOR DOCUMENT IMAGE TRANSFORMERMar 2022
Sample Annotations
Color Scheme
ColorMeaning
GreenTopics about the current paper
YellowTopics about other relevant references
BlueImplementation details/ maths/experiments
RedText including my thoughts, questions, and understandings
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A place to keep track of all the annotated papers.
au1206.github.io/
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annotated-papersdeep-learningmachine-learningmachine-learning-papersnlppaperresearch-papertransfer-learning
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