Lijie Chen ✓

@wjmzbmr1 · Berkeley, CA · joined 19 Jan 2016

Assistant professor at UC Berkeley EECS; reasoning at OpenAI Previously: Miller Postdoctoral Fellow at UC Berkeley, Ph.D. in MIT EECS

10 357Followers

448Following

478Posts total

473.7KViews on collected posts

Postingan terbaru

Lijie Chen ✓@wjmzbmr127 Jun

This is incredible!!! My first paper in my PhD back in 2018 was on this problem (getting a 2^{logstar n} dim bound); since then, I have been thinking about it on and off for at least 7 years. It's really crazy how things turned out. Last month at OpenAI, our model disproved the 95.5K views · 391 likes · 39 reposts · 6 replies Open on X →

Lijie Chen ✓@wjmzbmr126 Jun

Given a set of n points in d dimensions, the problems of finding the furthest pair and the closest pair require no explanation even to laymen. However, while finding the closest pair has a much more efficient algorithm, 183.6K views · 201 likes · 24 reposts · 3 replies Open on X →

Lijie Chen ✓@wjmzbmr121 May

1/ Today, an internal @OpenAI model has refuted Erdős’s unit distance conjecture — a research result that one could recommend “acceptance without any hesitation” to the Annals of Mathematics, one of the most prestigious journals in mathematics. We came across it in a side quest 125K views · 655 likes · 83 reposts · 9 replies Open on X →

Lijie Chen ✓@wjmzbmr16 Nov 2024

The ITCS 2025 accepted papers list is out: https://t.co/FUAqOWJJ9L 8.4K views · 44 likes · 5 reposts · 0 replies Open on X →

Lijie Chen ✓@wjmzbmr116 Oct 2024

Incredible breakthrough with a super beautiful proof! 13.8K views · 47 likes · 2 reposts · 1 replies Open on X →

Lijie Chen ✓@wjmzbmr115 Oct 2024

Can efficient quantum circuits behave like truly random unitaries to any efficient observer? The existence of such circuits, called pseudorandom unitaries (PRUs), has been open since 2017. In this paper w/ @RobertHuangHY, we show that PRUs exist: https://t.co/VgURAwhnwu Thread: 47.5K views · 229 likes · 26 reposts · 2 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

47.5K15 Oct

13.8K16 Oct

8.4K6 Nov

125K21 May

183.6K26 Jun

95.5K27 Jun

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

0.55%15 Oct

0.36%16 Oct

0.58%6 Nov

0.60%21 May

0.13%26 Jun

0.46%27 Jun

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

What the audience does

Likes76.9%1 567 in total

Reposts8.8%179 in total

Replies1.0%21 in total

Quotes1.1%22 in total

Bookmarks12.2%248 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.

Postingan terbaru

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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