Tianqi Chen ✓

@tqchenml · CMU · joined 07 May 2015

AssocProf @CarnegieMellon. Distinguished Eng @NVIDIA. Creator of @XGBoostProject, @ApacheTVM. Member https://t.co/QYyfjQNp4p, @TheASF. Views are on my own

21 272Followers

1 120Following

1 691Posts total

481.1KViews on collected posts

Posts recentes

Tianqi Chen ✓@tqchenml23 Sep

Submitting your work to #MLSys2027! 3.6K views · 30 likes · 2 reposts · 0 replies Open on X →

Tianqi Chen ✓@tqchenml23 Sep

Welcome to submit to MLSys 2027. I am thrilled to serve as a PC Co-Chair this year alongside Rashmi Vinayak. We are actively looking for cutting-edge research and industry track papers at the intersection of Machine Learning and Systems. https://t.co/pwldcGdbrs https://t.co/zVr90

12.4K views · 124 likes · 18 reposts · 0 replies Open on X →

Tianqi Chen ✓@tqchenml21 Sep

DeepSeek V4.1 structural tag now comes to XGrammar for reliable, native and fast tool calls 4.9K views · 30 likes · 3 reposts · 0 replies Open on X →

Tianqi Chen ✓@tqchenml21 Sep

🚀 More reliable agents with DeepSeek V4.1! XGrammar brings strict tool calling to SGLang & vLLM through Structural Tags, enforcing tool argument schemas in DeepSeek’s native format. See how the Structural Tag works 👇 https://t.co/VQuQXY85th Check out XGrammar 👇 https://t.co/29

23.4K views · 82 likes · 21 reposts · 4 replies Open on X →

Tianqi Chen ✓@tqchenml31 Aug

@tqchenml Everything will become deep learning. 1.2K views · 2 likes · 0 reposts · 1 replies Open on X →

Tianqi Chen ✓@tqchenml30 Aug

@tqchenml @XGBoostProject Can you add constraints to the vectors (like monotonicity)? Can the objective function vary by vector position? 1.9K views · 3 likes · 0 reposts · 0 replies Open on X →

Tianqi Chen ✓@tqchenml30 Aug

@tqchenml Love it! 1.7K views · 2 likes · 0 reposts · 0 replies Open on X →

Tianqi Chen ✓@tqchenml30 Aug

Checkout the latest XGBoost update "Introducing the XGBoost Vector-Leaf Model" from jiamin yuan and Rory Mitchell https://t.co/XOGcu2ZgIl https://t.co/PS77AJyCCO

106.4K views · 476 likes · 70 reposts · 7 replies Open on X →

Tianqi Chen ✓@tqchenml18 Aug

One thing that I am really excited about this TensorRT release is the first-class support for TVM-FFI, so we can bring custom DSL and agent generated kernels to TensorRT inference https://t.co/8yLGF5f1x5 9.8K views · 89 likes · 16 reposts · 1 replies Open on X →

Tianqi Chen ✓@tqchenml18 Aug

We just released TensorRT Model Connect in Public Preview. You can take a supported @huggingface model to end-to-end TensorRT inference in just two commands. No intermediate ONNX export, and the resulting bundle can run through native C++ APIs. We also built the entire project

98.7K views · 540 likes · 67 reposts · 33 replies Open on X →

Tianqi Chen ✓@tqchenml23 Jun

@tqchenml @SCSatCMU amazing work! any chance you're gonna publish the lecture recordings as well? 4.4K views · 9 likes · 0 reposts · 1 replies Open on X →

Tianqi Chen ✓@tqchenml23 Jun

We taught a brand-new mini-series this year at @SCSatCMU on Modern GPU Programming for ML Systems, as part of the ML Systems course, touching on fun questions like what data layout swizzling is, how to use 3D TMA, and state-of-the-art Blackwell programming. We released a curated

204.4K views · 1.8K likes · 291 reposts · 24 replies Open on X →

Tianqi Chen ✓@tqchenml23 Jun

Thanks @modal for compute support for the course, and the amazing course staff to make it happen. Finally the effort is made possible by the open source TIRx compiler effort lead by @bohanhou1998 and many other collaborators. 8.4K views · 33 likes · 0 reposts · 0 replies Open on X →

Em comparação com contas do mesmo porte

10 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.

Mediana de visualizações7 372esta conta980mediana para 10K–100K

Alcance, %34.66%esta conta3.84%mediana para 10K–100K

Engajamento, %0.60%esta conta1.53%mediana para 10K–100K

Métrica	Esta conta	Mediana para 10K–100K	Proporção
Mediana de visualizações por post	7 372	980	7.52×
Alcance (visualizações ÷ seguidores)	34.66%	3.84%	9.02×
Taxa de engajamento	0.60%	1.53%	0.39×

Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →

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

8.4K23 Jun

204.4K

4.4K

98.7K18 Aug

9.8K

106.4K30 Aug

1.7K

1.9K

1.2K31 Aug

23.4K21 Sep

4.9K

12.4K23 Sep

3.6K

Last 13 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.39%23 Jun

1.05%

0.23%

0.66%18 Aug

1.09%

0.53%30 Aug

0.12%

0.16%

0.25%31 Aug

0.49%21 Sep

0.67%

1.17%23 Sep

0.89%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.53%.

What the audience does

Likes46.0%3 246 in total

Reposts6.9%488 in total

Replies1.0%71 in total

Quotes0.6%44 in total

Bookmarks45.4%3 206 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.

Posts recentes

Em comparação com contas do mesmo porte

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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