Yaoyao(Freax) Qian

🥰Now is a #CoRL2024 Paper!

Just open-sourced TermHub!😍 A terminal-style academic homepage template built for AI workflows. Turn your CV into Markdown with ChatGPT / Claude, plug it into the template, and deploy. Guide term-hub.vercel.app/guide Repo github.com/H-Freax/TermHub

Yes! We are top paper of the week 🚀🚀🚀

@DengHokin 👏Amazing leadership on this project!

@RubyFreax This has been awesome!!!

Glad to have been part of this! There's genuinely a lot of interesting stuff in the data and tools if you're into video reasoning video-reason.com

@SonglinYang4 @MITEECS @thinkymachines 🤩🤩🤩Congrats!!!!!

Life update at the end of 2025: I’ve completed my PhD at @MITEECS and joined @thinkymachines to work on LLM archs

Off to San Diego for #NeurIPS2025 ! 🌴 I’ll be there the whole week (Dec 2–7). If you’re around and want to talk research, I’m always up for it. DM me if you want to meet up!

I quite like the new DeepSeek-OCR paper. It's a good OCR model (maybe a bit worse than dots), and yes data collection etc., but anyway it doesn't matter. The more interesting part for me (esp as a computer vision at heart who is temporarily masquerading as a natural language person) is whether pixels are better inputs to LLMs than text. Whether text tokens are wasteful and just terrible, at the input. Maybe it makes more sense that all inputs to LLMs should only ever be images. Even if you happen to have pure text input, maybe you'd prefer to render it and then feed that in: - more information compression (see paper) => shorter context windows, more efficiency - significantly more general information stream => not just text, but e.g. bold text, colored text, arbitrary images. - input can now be processed with bidirectional attention easily and as default, not autoregressive attention - a lot more powerful. - delete the tokenizer (at the input)!! I already ranted about how much I dislike the tokenizer. Tokenizers are ugly, separate, not end-to-end stage. It "imports" all the ugliness of Unicode, byte encodings, it inherits a lot of historical baggage, security/jailbreak risk (e.g. continuation bytes). It makes two characters that look identical to the eye look as two completely different tokens internally in the network. A smiling emoji looks like a weird token, not an... actual smiling face, pixels and all, and all the transfer learning that brings along. The tokenizer must go. OCR is just one of many useful vision -> text tasks. And text -> text tasks can be made to be vision ->text tasks. Not vice versa. So many the User message is images, but the decoder (the Assistant response) remains text. It's a lot less obvious how to output pixels realistically... or if you'd want to. Now I have to also fight the urge to side quest an image-input-only version of nanochat...

Thanks @_akhaliq for sharing our work! Aim and Grasp! AimBot introduces a new design to leverage visual cues for robots - similar to scope reticles in shooting games. Let's equip your VLA models with low-cost visual augmentation for better manipulation! aimbot-reticle.github.io

Introducing Eigent — the first multi-agent workforce on your desktop. Eigent is a team of AI agents collaborating to complete complex tasks in parallel. It is your long-term working partner with fullly customizable workers and MCPs. Public beta available to download for MacOS, Windows. 100% open-source on Github. Comment for 500 extra credits.

Excited to share our #ICML2025 paper, Hierarchical Equivariant Policy via Frame Transfer. Our Frame Transfer interface imposes high-level decision as a coordinate frame change in the low-level, boosting sim performance by 20%+ and enabling complex manipulation with 30 demos.

Owen will be presenting our poster for the paper Hierarchical Equivariant Policy via Frame Transfer at ICML Today (see lnkd.in/e-7p9Viq for details). If you are interested in equivariance and/or robotic manipulation please stop by!

inspired talk! #RSS2025

🤣First time at RSS! Happy to meet up and chat!

🥳Visual Tree Search of Web Agent has been accepted!

🔥 We introduce Multiverse, a new generative modeling framework for adaptive and lossless parallel generation. 🚀 Multiverse is the first open-source non-AR model to achieve AIME24 and AIME25 scores of 54% and 46% 🌐 Website: multiverse4fm.github.io 🧵 1/n

📢 (1/16) Introducing PaTH 🛣️ — a RoPE-free contextualized position encoding scheme, built for stronger state tracking, better extrapolation, and hardware-efficient training. PaTH outperforms RoPE across short and long language modeling benchmarks arxiv.org/abs/2505.16381

Proud to be part of this open-source effort after joining PathOnAI! 🌱 We hope this helps push web agent research toward more robust, interpretable, and deployable systems.

📄 Paper coming soon. 🎥 Video + docs in progress. 🧪 Explore the system now: Project: pathonai.org/projects/visua… Demo: visual-tree-search.pathonai.org Code: github.com/PathOnAI/Visua…

🚀 Excited to share VisualTreeSearch, my first project + upcoming paper with the open-source research group @PathOnAI ! It is a fully-deployed system for understanding test-time tree search in web agents, now open-source & demo-ready. 👇