Christopher Manning ✓

@chrmanning · Palo Alto · joined 17 Sep 2014

Founder @stanfordnlp & cs224n—Senior Fellow @StanfordHAI—Prof. CS & Linguistics @Stanford—GP @aixventureshq—MTS @moonlake—Australian🇦🇺—Do #NLProc & #AI 👋

168 746Followers

370Following

3 029Posts total

304.8KViews on collected posts

Against accounts of the same size

8 posts from the last 90 days, next to the 100K–1M follower range. shown widely, but few of those viewers react.

Median views29 579this account4 505median for 100K–1M

Reach, %17.53%this account1.88%median for 100K–1M

Engagement, %0.95%this account1.48%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	29 579	4 505	6.57×
Reach (views ÷ followers)	17.53%	1.88%	9.32×
Engagement rate	0.95%	1.48%	0.64×

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

23.6K18 Aug

31.9K19 Aug

100.1K23 Aug

6.4K

81.7K

1.9K

30.6K24 Aug

28.6K25 Aug

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.79%18 Aug

1.37%19 Aug

1.05%23 Aug

1.07%

0.84%

2.18%

0.12%24 Aug

0.73%25 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.48%.

What the audience does

Likes52.4%2 409 in total

Reposts5.1%233 in total

Replies1.3%60 in total

Quotes0.4%17 in total

Bookmarks40.8%1 875 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

Substantive ML discussion on Twitter. Like in the 2010s. Feeling blessed. 😊 28.6K views · 199 likes · 2 reposts · 8 replies 25 Aug 2026 @RolandMemisevic @akarshkumar0101 @chrmanning I think that's a good bet too. Actually let me clarify that I don't really think of SMT as "distill transformers." It's joint optimization of a memory-bottlenecked transformer and an RNN. So it may be closer to your bet than it seems? 30.6K views · 37 likes · 0 reposts · 0 replies 24 Aug 2026 @chrmanning @akarshkumar0101 @phillip_isola Another cool connection is the ability to parallelize GRUs over the sequence length for both forward and backward passes, allowing pretraining at scale without teacher forcing. As for example in this paper! https://t.co/9QB0cr7rqf 1.9K views · 36 likes · 5 reposts · 1 replies 23 Aug 2026 When teaching CS224N, I thought it important to introduce students to a broad neural toolbox – not just transformers but FFNs, CNNs, LSTMs, tree-recursive NNs, BiDAF QA nets, highway nets, …. I think the resurgence of work using recurrence shows the importance of this approach. 81.7K views · 630 likes · 40 reposts · 14 replies 23 Aug 2026 Paper: https://t.co/IoDcRINaAL This is one of a whole bunch of recent papers reviving study of recurrent neural networks. One weird omission is not testing LSTM RNNs. Surely they remain the canonical successful RNN architecture? Another completely uninvestigated thing is the 6.4K views · 59 likes · 5 reposts · 4 replies 23 Aug 2026 Pretraining Recurrent Networks without Recurrence by @akarshkumar0101 & @phillip_isola is a great paper! It makes an end-run around the problems of RNNs via a transformer teacher to learn good predictive state representations & supervised learning of a memory transition 100.1K views · 917 likes · 112 reposts · 16 replies 23 Aug 2026 Transformers are Inherently Succinct by Pascal Bergsträßer, Ryan Cotterell & Anthony Widjaja Lin is an interesting contribution. Various work (Hahn 2020, Li & Cotterell 2025 i.a.) has shown that transformers are less powerful than RNNs … yet somehow they do so well in pr 31.9K views · 375 likes · 51 reposts · 8 replies 19 Aug 2026 The Bay Area’s AI corporate titans still just haven’t come to terms with the fact that it’s not that the public has a negative view of or fear of AI. It’s that the public has a negative view of _them_. But I don’t imagine that they’re likely to go on a similar listening tour…. 23.6K views · 156 likes · 18 reposts · 9 replies 18 Aug 2026