Uploaded June 2021 | Updated September 2026, 11 hours ago
This is all about where to find Machine Learning research and how to find Machine Learning research papers! Finding ML papers can be a bit of a pain without the right tools. But with these sites, it is easy to find Machine Learning papers! I talk about sites like Google Scholar, Arxiv, Papers with Code and more. With these sites, you shouldn't have to wonder where to find Machine Learning research papers anymore:
Papers With Code: paperswithcode.com
Machine Learning Subreddit: reddit.com/r/MachineLearning
Google Scholar: scholar.google.com
Arxiv: arxiv.org
DeepMind Research: deepmind.com
OpenAI Research: openai.com/blog/tags/research
I hope this helped you learn where to find ML research!
This is all about where to find Machine Learning research and how to find Machine Learning research papers! Finding ML papers can be a bit of a pain without the right tools. But with these sites, it is easy to find Machine Learning papers! I talk about sites like Google Scholar, Arxiv, Papers with Code and more. With these sites, you shouldn't have to wonder where to find Machine Learning research papers anymore:
Papers With Code: paperswithcode.com
Machine Learning Subreddit: reddit.com/r/MachineLearning
Google Scholar: scholar.google.com
Arxiv: arxiv.org
DeepMind Research: deepmind.com
OpenAI Research: openai.com/blog/tags/research
I hope this helped you learn where to find ML research!





![Self-Supervised RL - Learning Without Data [Zero to Paper]
Inverse Reinforcement Learning with Natural Language Goals (LangGoal IRL) offers a way to do sample-efficient IRL and a way to generalize using self-supervised learning. The paper is novel and is a step forward for general AI and ML algorithms. Though it has its cons, I think it is one of the better papers out there that cover RL, IRL, NLP, and generalization.
Zero to Paper playlist: https://www.youtube.com/playlist?list=PL_49VD9KwQ_ONxENRk11jFEI3_pqAwaug
Inverse Reinforcement Learning video: https://www.youtube.com/watch?v=qo355ALvLRI
Paper covered: https://arxiv.org/pdf/2008.06924.pdf Self-Supervised RL - Learning Without Data [Zero to Paper]](https://i.ytimg.com/vi/CDKsa06xU0o/mqdefault.jpg)




