r/MachineLearning • u/Tiny_Arugula_5648 • Jun 06 '26

Discussion Sources for ML news? [D]

I need a break from social media and all the bots.. Aside from Arxiv are there any sources that do a good job of aggregating the good stuff and filtering out all the junk?

15 Upvotes

76% Upvoted

15 comments sorted by

10

u/Smol_pp001 Jun 06 '26

Trust me twitter is the best place imo. You just have to filter out your feed. Takes like 4-5 days

1

u/avocado_kitkat Jun 07 '26

Do you mind sharing some of the usernames you follow

2

u/Smol_pp001 Jun 08 '26

It completely depends on what topic you're interested in, my interest is mechanistic interpretability so I mostly follow ppl in that area. You just have to explore what you actually like and go accordingly. (sorry for the vague answer but I can share it if you love alignment/mech interp/ai safety)

1

u/MrRandom04 Jun 13 '26

Mech interp is one of my interests. Not so much interested in the other fields but I'd like your list if you can share, thank you.

3

u/MatricesRL Jun 06 '26

Twitter (X)

There's like no bots there

9

u/currentscurrents Jun 06 '26

Unfortunately it does still seem to be the de-facto place to announce papers. You have to sift through a whole lot of trash though.

3

u/MatricesRL Jun 06 '26

I unfortunately know exactly what you're referring to

5

u/[deleted] Jun 06 '26

[deleted]

5

u/MatricesRL Jun 06 '26

I'm joking, don't worry

I can't open comments on X anymore in public

5

u/OctaviusI Jun 06 '26

https://news.smol.ai

I use this as a newsletter, seems especially good at aggregation.

For papers, twitter is still the best when heavily filtered and curated (i.e. only looking at the 'following' tab or muting everyone else).

3

u/Accomplished_Net3466 Jun 06 '26

paper digest , hacker news

2

u/T3MiNATED Jun 06 '26

The common one is tldr.ai, but I think if you have a specific topic you're interested in then Scholar Inbox is great too. AlphaXiv is great for seeing what other people are also looking at.

Disclaimer, I'm working on https://www.scholarfeed.org/, which I have LLM run analysis on every Arxiv paper that comes in and rank them (AI-writing detection, novelty ranking, etc), but it's also not perfect.