Jure Leskovec ✓

@jure · Stanford, CA · joined 12 Aug 2007

Professor of #computerscience @Stanford; Co-founder at https://t.co/hhm1j5wP0f #machinelearning #graphs.

45 059Followers

428Following

1 522Posts total

77.8KViews on collected posts

Latest posts

Jure Leskovec ✓@jure19 Aug

Excited to see this out! Relational learning needs strong benchmarks, standardized evaluation, and easy ways to bring methods to real-world relational data. 4.2K views · 24 likes · 2 reposts · 1 replies Open on X →

Jure Leskovec ✓@jure18 Aug

We’re happy to announce our first release in relational learning at Prior Labs, continuing our commitment to open science. We open-source three pieces of software that we expect to accelerate research in the field towards meaningful, real-world impact. First and foremost, we ht 8.6K views · 45 likes · 11 reposts · 0 replies Open on X →

Jure Leskovec ✓@jure13 Aug

Fun conversation with @ItaiYanai on @nightsciencepod about what happens when AI starts doing science: agents that find patterns, generate hypotheses, and try to falsify them with more data. We also got into taste, judgment, and where human scientists still matter most. 13.8K views · 80 likes · 10 reposts · 2 replies Open on X →

Jure Leskovec ✓@jure11 Aug

How would you let the LLM dream? [...] In a sense, to replay things, organize them, think about them so that tomorrow when we wake up, our thoughts are more organized than just input-output-input-output. –Jure Leskovec, Stanford Professor, @jure https://t.co/CzSbIgX4QY 17.4K views · 24 likes · 4 reposts · 3 replies Open on X →

Jure Leskovec ✓@jure28 Jul

Exciting milestone for @KexinHuang5 and the @phylo_bio team. Putting AI scientist systems directly in the hands of discovery scientists is where the next big gains in biomedical AI will come from. 6K views · 33 likes · 4 reposts · 5 replies Open on X →

Jure Leskovec ✓@jure13 Jul

@jure @Nature It took 3 years??? How I didnt even know it was still a preprint 250 views · 1 likes · 0 reposts · 1 replies Open on X →

Jure Leskovec ✓@jure13 Jul

Paper: https://t.co/IcYq4PVYC9 Code: https://t.co/xFKZaQol5X Thanks so much to the team @YanayRosen @yusufroohani @StephenQuake! 1.2K views · 2 likes · 0 reposts · 0 replies Open on X →

Jure Leskovec ✓@jure13 Jul

Excited to share that our Universal Cell Embedding (UCE) paper is published in @Nature ! Single-cell RNA sequencing data gives us an unprecedented look into the diversity of cell biology, but analysis has often been limited to the specific dataset or atlas that was collected. 18.1K views · 246 likes · 45 reposts · 5 replies Open on X →

Jure Leskovec ✓@jure13 Jul

We designed and trained the UCE foundation model so that any new data, from any disease, tissue or species, could be mapped into the same universal representation space, without fine tuning or retraining. 1.9K views · 6 likes · 0 reposts · 1 replies Open on X →

Jure Leskovec ✓@jure13 Jul

UCE connects molecular and cellular scales of biology. Genes are more than just columns in an expression matrix: in UCE, they are encoded according to the proteins they produce, using ESM, embedding novel species not seen during training, across 100Ms of years of evolution. 1.9K views · 5 likes · 0 reposts · 1 replies Open on X →

Jure Leskovec ✓@jure6 Jul

Modern multimodal models aren't a single decode loop anymore; they're composite. M* is one runtime that serves them all, and it matches or beats every specialized system: up to 2.7× on omni TTS, 12.5× on world-model rollouts. Learn more here: https://t.co/3MwvdJiJaQ https://t.co/ 4.3K views · 28 likes · 6 reposts · 1 replies Open on X →

Against accounts of the same size

11 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views4 314this account924median for 10K–100K

Reach, %9.57%this account3.62%median for 10K–100K

Engagement, %0.67%this account1.52%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	4 314	924	4.67×
Reach (views ÷ followers)	9.57%	3.62%	2.64×
Engagement rate	0.67%	1.52%	0.44×

Others in this range → Compare with another account → How these benchmarks are built →

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

4.3K6 Jul

1.9K13 Jul

1.9K

18.1K

1.2K

250

6K28 Jul

17.4K11 Aug

13.8K13 Aug

8.6K18 Aug

4.2K19 Aug

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.81%6 Jul

0.31%13 Jul

0.42%

1.64%

0.16%

0.80%

0.70%28 Jul

0.19%11 Aug

0.67%13 Aug

0.70%18 Aug

0.64%19 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes58.8%494 in total

Reposts9.8%82 in total

Replies2.4%20 in total

Quotes1.2%10 in total

Bookmarks27.9%234 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.

Latest posts

Against accounts of the same size

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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