Yang Song ✓

@DrYangSong · joined 12 Jul 2014

Research Principal of MSL

15 953Followers

967Following

257Posts total

1.1MViews on collected posts

Latest posts

Yang Song ✓@DrYangSong3 Sep

Muse Spark 1.3 is here! The leap from 1.0 to 1.3 is nothing short of a miracle, and it took a lot of magic to make it happen. So proud of our team of magicians who sparked this incredible leap. And we are just getting started! 10.3K views · 125 likes · 10 reposts · 5 replies Open on X →

Yang Song ✓@DrYangSong10 Aug

I’m personally very excited to see us take this step. I’ve long believed that the power of AGI should be broadly distributed, and this is the first of many moves at MSL toward making superintelligence accessible to everyone. 27.1K views · 229 likes · 16 reposts · 2 replies Open on X →

Yang Song ✓@DrYangSong8 Apr

Today we’re excited to release Muse Spark. It’s our first end-to-end test of the new stacks we’ve built at MSL, and a true testament to this incredible team. We’re eager to learn from your feedback! https://t.co/PPWBgewWQx 16.1K views · 283 likes · 15 reposts · 6 replies Open on X →

Yang Song ✓@DrYangSong29 Oct 2025

Applications change, but the principles are enduring. After a year's hard work led by @JCJesseLai, we are really excited to share this deep, systematic dive into the mathematical principles of diffusion models. This is a monograph we always wished we had. 59.5K views · 445 likes · 43 reposts · 7 replies Open on X →

Yang Song ✓@DrYangSong29 Oct 2025

Tired to go back to the original papers again and again? Our monograph: a systematic and fundamental recipe you can rely on! 📘 We’re excited to release 《The Principles of Diffusion Models》— with @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon. It traces the core ht

923K views · 2.4K likes · 499 reposts · 51 replies Open on X →

Yang Song ✓@DrYangSong5 Aug 2025

Very excited to see this model released to the open-source community. It's still hard to believe that our latest techniques allow it to be so incredibly powerful yet so remarkably small. 23.9K views · 136 likes · 2 reposts · 3 replies Open on X →

Yang Song ✓@DrYangSong5 Aug 2025

super excited to have contributed to gpt-oss. We have put a lot of love into both training the model and making the developer examples, check them out: https://t.co/zaiZ4b9Ski 36.9K views · 180 likes · 9 reposts · 9 replies Open on X →

Against accounts of the same size

2 posts from the last 90 days, next to the 10K–100K follower range. shown to more people than peers of the same size.

Median views18 672this account924median for 10K–100K

Reach, %117.04%this account3.62%median for 10K–100K

Engagement, %1.14%this account1.52%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	18 672	924	20.2×
Reach (views ÷ followers)	117.04%	3.62%	32.3×
Engagement rate	1.14%	1.52%	0.75×

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

36.9K5 Aug

23.9K

923K29 Oct

59.5K

16.1K8 Apr

27.1K10 Aug

10.3K3 Sep

Last 7 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%5 Aug

0.59%

0.33%29 Oct

0.84%

1.89%8 Apr

0.91%10 Aug

1.36%3 Sep

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

What the audience does

Likes51.3%3 801 in total

Reposts8.0%594 in total

Replies1.1%83 in total

Quotes0.9%64 in total

Bookmarks38.7%2 873 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.