Heng Yu

PhD student @Stanford

[Cyrus (Zikai) Zhou @cyruszzhou]

Excited to share that SatIR has been accepted to COLM 2026! 🎉 Grateful to my incredible collaborators across Stanford and Mayo Clinic. The core idea: for high-stakes retrieval, don't just ask "does this sound relevant?" - ask "is this actually possible?"

Also accepted - DataSTORM from @StanfordOVAL led by @ShichengGLiu , an LLM agent that runs deep research over massive structured databases, turning raw data into coherent analytical narratives (and beating ChatGPT Deep Research): https://t.co/vHY3gGtd9e

[Cyrus (Zikai) Zhou @cyruszzhou]

🔎 In high-stakes domains, a missed search result is not just a search error - it can mean a missed opportunity, delayed decision, or denied service.

Yet most retrieval systems still rank by keywords and embeddings. They can surface candidates that look relevant while missing those that actually satisfy the constraints.

What if an agent could turn those constraints into a retrieval tool that searches for viable options directly?

🌐 Project: https://t.co/sdRZD6QCHt
📄 Paper: https://t.co/GfAg16TI2e

With @Yufei_1001, @kelakexyl, @YuChiangWang1, @ChiehJuChao1, and @MonicaSLam. Grateful to our collaborators across Stanford and Mayo Clinic, and to the broader @stanfordnlp and @StanfordHAI communities that helped shape the environment for this work.

#InformationRetrieval #AIAgents

<🧵1/n | 𝗦𝗮𝘁𝗜𝗥>

[Haoyu Xiong @Haoyu_Xiong_]

Mobile manipulation is not just putting arms on wheels. It introduces a different class of challenges, such as partial observability, whole-body interface design.

However, researchers are often held back by hardware setup before they can get to the actual research problems.
I recently wrote a tutorial, https://t.co/tZDCeXGWzE to make the process easier.
With support from hardware vendors, you can now purchase an out-of-box hardware kit directly, without having to build everything from scratch. We also provide a plug-and-play codebase for the robot control, teleoperation, data collection, model training, and inference.

Simple Mobile aims to make mobile manipulators more accessible, save you time, and help you get to the **research part** faster.

[Y Combinator @ycombinator]

Origami Robotics is building high-DOF robotic hands with in-joint motors and a co-designed data-collection glove to eliminate the embodiment gap by collecting high-quality, real-world data at scale.

Congrats on the launch, @DanielXieee and @QuanliangX!

https://t.co/BkzyfawSrg

[Heng Yu @Heng54578593]

Huge congrats!

[Quanting Xie @DanielXieee]

A few days ago we got in YC W26, and here is we are working on.

Building hardware is hard, but I really like a quote from @yukez: “People who are really serious about robot learning should make their own robot hardware.”

[Haoyu Xiong @Haoyu_Xiong_]

Your bimanual manipulators might need a Robot Neck 🤖🦒

Introducing Vision in Action: Learning Active Perception from Human Demonstrations

ViA learns task-specific, active perceptual strategies—such as searching, tracking, and focusing—directly from human demos, enabling robust visuomotor policies under visual occlusions. 🧵👇

[Laszlo A Jeni (PhD) @LaszloJeni]

📌 If you're at #CVPR2024 this week, please stop by our posters:
- 3D-LFM: Lifting Foundation Models (Poster #78)
🗓️ Thu, 10:30am
🔗 https://t.co/MzmiInTazE
- CoGS: Controllable Gaussian Splatting (Poster #200)
🗓️ Fri, 10:30am
🔗 https://t.co/emtxeHuDcq

[Laszlo A Jeni (PhD) @LaszloJeni]

Check out "𝐂𝐨𝐆𝐒: 𝐂𝐨𝐧𝐭𝐫𝐨𝐥𝐥𝐚𝐛𝐥𝐞 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐒𝐩𝐥𝐚𝐭𝐭𝐢𝐧𝐠" at #CVPR2024! Simplifies 3D object re-animation and scene manipulation. A collaboration between @roboVisionCMU and @fujitsulabs. Learn more 👉 https://t.co/YxouBOErx2 #GaussianSplatting

[Laszlo A Jeni (PhD) @LaszloJeni]

It was fantastic to connect with current &amp; past minds of CMU CUBE Lab at #CVPR2023 (w/ Joel Julin, Chaoyang Wang, @Heng54578593, @srph25, &amp; @ARevanur)! Kudos to the team for brilliant papers! #GoSmithHall @SCSatCMU

[Laszlo A Jeni (PhD) @LaszloJeni]

Join us now at West Exhibition Hall A for our poster on “Unsupervised Style-Based Explicit 3D Face Reconstruction From Single Image” with @Heng54578593 and @srph25 .

Paper: https://t.co/2LrZlCadml

#GenerativeCV #3DFaceReconstruction #ComputerVision #AI #CVPR2023

[Laszlo A Jeni (PhD) @LaszloJeni]

Explore anatomically precise &amp; controllable facial representations with CoNFies, using NeRF &amp; AFAR! Code &amp; project now online, collab w/ @Heng54578593 &amp; Koichiro Niinuma:
Code: https://t.co/rJuVppuKVU
Project: https://t.co/xEf0o9fw11
#NeRF #CoNFies #AI #DeepLearning #OpenSource

[Laszlo A Jeni (PhD) @LaszloJeni]

🎉 2/2 papers accepted at #CVPR2023, one as a highlight!🌟
Wang et al.: "Deformable NeRF with Optical Flow Supervision" (https://t.co/EdBNhxOfqQ)
Yu et al.: "DyLiN: Making Light Field Networks Dynamic" (https://t.co/94UwaEOzrP)
#NeRF #OpticalFlow #LightFields #AI #computervision

[Heng Yu @Heng54578593]

@whshkan Awesome job tangerine!