Alan Chen

making robots & myself continually learn; CS (Turing Scholar) @UTAustin

[Alan Chen @AlanJiaqiChen]

@hongyangzh @UTCompSci @EagleCorp Congrats! Welcome to atx.

[Jiaheng Hu @JiahengHu1]

Super fun chatting with @micoolcho and @DJiafei!

I'll also be presenting this work at the CoRL Late-Breaking Results today from 12:30 to 1:30! Come and chat if you want to know more about it!

[Alan Chen @AlanJiaqiChen]

Found a lost Honor phone in the Hilton area and thought the best way to find the owner would be to post it on here. I’ll turn it at the registration and you can find it there if it belongs to you.
#CoRL2026

[Alan Chen @AlanJiaqiChen]

@HarshSensei excited too see it!

[Alan Chen @AlanJiaqiChen]

@theSamPadilla lol, I was the one behind the kiosk while you were registering. Yea no clue…

[Alan Chen @AlanJiaqiChen]

@massssss7262 See you there!

[Alan Chen @AlanJiaqiChen]

@horiyuki42 See you there!

[Alan Chen @AlanJiaqiChen]

Heading 20 minutes from my dorm to #CoRL2026!

Will be helping out as a volunteer alongside my wonderful LARG labmates @JefferyXu4, @JiahengHu1, and more!

Happy to chat + feel free to DM me about robot learning, auto-research, VLA, or anything else.

[Alan Chen @AlanJiaqiChen]

@wltnwang Welcome to atx! :)

[RoboPapers @RoboPapers]

Full episode dropping soon!

Geeking out with @JiahengHu1 and @SteveTod1998 on “SimEX: Simulation-Integrated Robotics AutoResearch.”

https://t.co/SiUXjTNRWx

Co-hosted by @micoolcho and @DJiafei

[Alan Chen @AlanJiaqiChen]

Crazy how good LLMs are.

[Andrew Curran @AndrewCurran_]

OpenAI has announced to three new discoveries in mathematics, computer science, and physics:
- Local smoothing and the Kakeya conjecture
- The Exponential Time Hypothesis is false
- Existence of quantum chromodynamics and completions of the Standard Model

[Alan Chen @AlanJiaqiChen]

Super cool stuff. Expected nothing less from @cranialxix and team!!!

[Richard Socher @RichardSocher]

Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.

• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months

Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

[Alan Chen @AlanJiaqiChen]

Another banger from Alan again. Latent forcing was already super cool!

Always wondered if there was a more efficient way to approach tokenization, excited to see this direction be explored.

[Alan Baade @BaadeAlan]

1/ The tokenizer is a new scaling axis!

We introduce an approach for diffusable representation learning that's principled, scalable, and works when DINO/LeJEPA collapse.

We get joint tokenizer+diffusion scaling laws and it's compute-optimal vs raw diffusion

w/ @drfeifei @GordonWetzstein @jcjohnss @ericryanchan @vincesitzmann @KyleSargentAI

Thread, Paper, and Blogpost below

[Alan Chen @AlanJiaqiChen]

Cool stuff!!!

[Peter Stone @PeterStone_TX]

Fun feature by IEEE!
https://t.co/mtzaIM8sqv

[Chenfeng_X @Chenfeng_X]

While exploring diffusion language models (DLMs), we kept asking ourselves: given speculative decoding, a lossless acceleration technique, why do we still need DLMs? 🤔 Our latest work, ORL, tries to answer this question: AR optimizes intelligence 👆, speculative decoding optimizes speed 👉, and DLMs optimize the Pareto frontier of speed and intelligence 🚀. Through co-design across the algorithms, the training and inference engine, and the kernels, ORL pushes out a new Pareto frontier of intelligence and speed. Similar performance, much faster than speculative decoding. You say lossy spec? ORL-DLM is better too! 😎

🌐 Project + live demos: https://t.co/pi87MopVSc

[Caroline Wang @CarolineWang98]

[1/4] I’m pleased to share that the JaxAHT paper has finally been released, and the library has received a v1.1 update! I wish I had a tool like this in the beginning of my PhD.
What’s new 👇
Codebase: https://t.co/5UyOY4NUYV
Preprint: https://t.co/Bs5db0rMO7

[Alan Chen @AlanJiaqiChen]

@BetaTomorrow great post! There's so many cool challenges such as knowing what info is useful to sample/adapt, how we quantify what is better and w/ efficency (a powerful sim may approximate reality but doesn't matter if not slow and expensive), how deep an agent should investigate (RLM), etc

[Alan Chen @AlanJiaqiChen]

@_onionesque DMed

[Alan Chen @AlanJiaqiChen]

@a1zhang @stateofai congrats bro

[Alan Chen @AlanJiaqiChen]

@JaidevShah4 Emailed! Already in the SR candidate matching process and have super relevant experience with post-training and continual learning.