Skip to content

Papers, repositories, and other resources from the Bell Labs of X

License

Notifications You must be signed in to change notification settings

gerred/awesome-hensen

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
 
 
 
 

Repository files navigation

awesome-hensen

Papers, code, notebooks, documentation, tutorials, and the ideas and implementations made by, in the orbit of, and of interest to the group of (semi-)anonymous humans and AI that has been described as the "modern day bell labs".

contributing

i'm still unpacking all of my resources and curating! with multiple lines of research happening between a few dozen people flowing in and out and often asynchronous, but continuous context, things will get missed. open a PR. this is a growing repository, not currently inclusive of past, present, and future work. this repo likes:

  • research and engineering to solve problems
  • in depth resources made with care and love
  • a general avoidance of product placements, proprietary tools and services
  • things I ultimately find are tasteful additions
  • obsessive notion drops and blog posts are high signal

where available, direct references to the authors and creators are provided.

out of scope for this repo are the many excellent resources of the "standard" papers, how to learn ML, etc. I welcome "other topics" PRs to those lists, but I myself do not track that other than the few that I directly send others that more fit this format.

this is not an official work or endorsed in any way. i was looking for a corpus of ideas and resources to separate the signal from noise for others, and this is my attempt at doing so.

license

CC0 1.0 Universal - this repository provides resources that are under a variety of open licensing. as such, this curation is in the public domain.

background

research of interest

deepseek

explainers

papers

rwkv

still reading background materials but of particular interest - stay tuned

performance

mechanistic interpretability

reinforcement learning

vision language models

this is my jam, a massive amount coming here shortly

other topics

attribution

again, this is a curation, so you should cite the resources themselves, but if you really want to cite this, cite it as:

@misc{gerred_awesome_hensen,
  author       = {Gerred Dillon},
  title        = {Awesome Hensen},
  year         = {2025},
  publisher    = {GitHub},
  journal      = {GitHub repository},
  howpublished = {\url{https://github.com/gerred/awesome-hensen}},
}

About

Papers, repositories, and other resources from the Bell Labs of X

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published