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Sebastian Riedel (@riedelcastro@sigmoid.social)

@riedelcastro · London, England · joined 21 Sep 2009

Researcher in NLP/ML @deepmind, @ucl_nlp, @riedelcastro@sigmoid.social on Mastodon

16 247Followers
453Following
1 917Posts total
75.3KViews on collected posts

Derniers posts

Frontier models can do this stuff, but also not! Opinions differ on how much we even want this (CC @geoffreyirving), but understanding the patterns will be critical regardless. Been a pleasure to work with Latent Reasoning Dream Team @soheeyang_ @megamor2 @KassnerNora! 7.2K views · 28 likes · 7 reposts · 0 replies Open on X →
🚨 New Paper 🚨 Can LLMs perform latent multi-hop reasoning without exploiting shortcuts? We find the answer is yes – they can recall and compose facts not seen together in training or guessing the answer, but success greatly depends on the type of the bridge entity (80%+ for https
GIF
47.4K views · 205 likes · 51 reposts · 7 replies Open on X →
Amazing progress @YuxiangJWu and @zhengyaojiang, and great to see the impact of "agent scaffolding" given a base model. 3.9K views · 15 likes · 4 reposts · 0 replies Open on X →
Super proud to have been able to work with you @PSH_Lewis! Does this improve my Bacon number? 3.4K views · 16 likes · 1 reposts · 0 replies Open on X →
@PSH_Lewis https://t.co/M6rMbHYUx6
3.9K views · 6 likes · 0 reposts · 0 replies Open on X →
"just put the corpus into the context"! Long context models can already match or beat various bespoke pipelines and infra in accuracy on non-trivial tasks! Hadn't expected this so soon, and honestly was hoping to milk RAG impact for a little longer 🤪 9.6K views · 49 likes · 17 reposts · 3 replies Open on X →
Interested in language, knowledge and reasoning? Come to work with me and others at @DeepMind and its language group as a research scientist! Apply here: https://t.co/uiONcZ7y9Q 0 views · 258 likes · 45 reposts · 4 replies Open on X →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

9.6K21 Jun
3.9K6 Sep
3.4K
3.9K14 Oct
47.4K27 Nov
7.2K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.72%21 Jun
0.16%6 Sep
0.50%
0.49%14 Oct
0.55%27 Nov
0.49%

Reactions — likes, reposts, replies and quotes — divided by views.

What the audience does

Likes71.7%319 in total
Reposts18.0%80 in total
Replies2.2%10 in total
Bookmarks8.1%36 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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