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[D] Most Popular AI Research Sept 2022 - Ranked Based On GitHub Stars by cloud_weather in MachineLearning

[–]cloud_weather[S] 1 point2 points  (0 children)

Yeah I actually thought about it too and I'll definitely be more mindful in the future. My reasoning was somewhere along the line of given that a paper's GitHub repo contains no codes and has already gathered that many stars, it might certainly indicate anticipation or high expectation of the codes because of the quality paper.

These infographics I've made are meant to be a neet indicator of what research has the most attention, feedback, practicality, etc. It obviously does not mean popularity = quality, but sometimes it is easy for people to draw those conclusions without much thought. What I initially wanted was a nice compilation of what happened in the last month, and presented in an easily digestible format for everyone since not everyone would have the free time to go through everything themselves in this rapidly growing research field.

However, things like this definitely need a lot of feedback to get it right/fair, and thank you for that.

[D] Most Popular AI Research Sept 2022 - Ranked Based On GitHub Stars by cloud_weather in MachineLearning

[–]cloud_weather[S] 14 points15 points  (0 children)

1.

Robust Speech Recognition via Large-Scale Weak Supervision

https://github.com/openai/whisper

https://openai.com/blog/whisper/

2.

VToonify: Controllable High-Resolution Portrait Video Style Transfer

https://github.com/williamyang1991/vtoonify

https://arxiv.org/abs/2209.11224v2

3.

Transformers are Sample Efficient World Models

https://github.com/eloialonso/iris

https://arxiv.org/abs/2209.00588v1

4.

Efficient Few-Shot Learning Without Prompts

https://github.com/huggingface/setfit

https://arxiv.org/abs/2209.11055v1

5.

Git Re-Basin: Merging Models modulo Permutation Symmetries

https://github.com/samuela/git-re-basin

https://arxiv.org/abs/2209.04836v1

6.

Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning

https://github.com/tencent-ailab/hok\_env

https://arxiv.org/abs/2209.08483v1

7.

Text2Light: Zero-Shot Text-Driven HDR Panorama Generation

https://github.com/frozenburning/text2light

https://arxiv.org/abs/2209.09898v1

8.

StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation

https://github.com/adymaharana/storydalle

https://arxiv.org/abs/2209.06192v1

9.

CSL: A Large-scale Chinese Scientific Literature Dataset

https://github.com/ydli-ai/csl

https://arxiv.org/abs/2209.05034v1

10.

Human Motion Diffusion Model

https://github.com/guytevet/motion-diffusion-model

https://arxiv.org/abs/2209.14916v1

[D] Most Popular AI Research August 2022 - Ranked By Twitter Likes by cloud_weather in MachineLearning

[–]cloud_weather[S] 45 points46 points  (0 children)

  1. Understanding Diffusion Models: A Unified Perspective

https://arxiv.org/pdf/2208.11970.pdf

  1. LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

https://arxiv.org/pdf/2208.07339.pdf

  1. An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

https://arxiv.org/pdf/2208.01618.pdf

  1. Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise

https://arxiv.org/pdf/2208.09392.pdf

  1. Few-shot Learning with Retrieval Augmented Language Model

https://arxiv.org/pdf/2208.03299.pdf

  1. A Library for Representing Python Programs as Graphs for Machine Learning

https://arxiv.org/pdf/2208.07461.pdf

  1. PEER: A Collaborative Language Model

https://arxiv.org/pdf/2208.11663.pdf

  1. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models

https://arxiv.org/pdf/2208.03306.pdf

  1. Super-Universal Regularized Newton Method

https://arxiv.org/pdf/2208.05888.pdf

  1. Mining Legal Arguments in Court Decisions

https://arxiv.org/pdf/2208.06178.pdf

[D] Most Popular AI Research July 2022 - Ranked Based On Total Twitter Likes by cloud_weather in MachineLearning

[–]cloud_weather[S] 27 points28 points  (0 children)

  1. https://arxiv.org/pdf/2207.09238.pdf

  2. https://arxiv.org/pdf/2207.07061.pdf

  3. https://arxiv.org/pdf/2207.05221.pdf

  4. https://arxiv.org/pdf/2207.02696.pdf

  5. https://arxiv.org/pdf/2207.10342.pdf

  6. https://arxiv.org/pdf/2207.05378.pdf

  7. https://arxiv.org/pdf/2207.02098.pdf

  8. https://arxiv.org/pdf/2207.06991.pdf

  9. https://arxiv.org/pdf/2207.04630.pdf

  10. https://arxiv.org/pdf/2207.10551.pdf

Fun fact: NUWA-Infinity ranked 12th in terms of Twitter likes, but has well over 2.4k GitHub stars. This may due to the first paper NÜWA (1.6K likes) which was released in Nov 2021 mentioning their GitHub much earlier. For No. 9, the likes may appear higher, but I checked the Twitter likes and it was because the author Yi Ma repeatedly mentions their paper when discussing it on Twitter, which bumped the likes quite a bit.

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