Zhengzhong Tu

🎉 [𝗡𝗲𝘂𝗿𝗜𝗣𝗦 𝟮𝟬𝟮𝟱] 𝗣𝗮𝗽𝗲𝗿 𝗔𝗰𝗰𝗲𝗽𝘁𝗲𝗱 𝗮𝗻𝗱 𝗖𝗼𝗱𝗲 𝗥𝗲𝗹𝗲𝗮𝘀𝗲!

Not everyone is a photo pro — even with advanced AI tools. Restoring an image to professional grade often requires either 𝘥𝘦𝘦𝘱 𝘱𝘩𝘰𝘵𝘰𝘨𝘳𝘢𝘱𝘩𝘺 𝘦𝘹𝘱𝘦𝘳𝘵𝘪𝘴𝘦 or 𝘣𝘳𝘰𝘢𝘥 𝘬𝘯𝘰𝘸𝘭𝘦𝘥𝘨𝘦 of how to combine many different AI models.

🙋 𝗦𝗼 𝘄𝗲 𝗮𝘀𝗸𝗲𝗱 𝗼𝘂𝗿𝘀𝗲𝗹𝘃𝗲𝘀: Can we build a restoration agent that fully automates this process — no domain expertise required?

To answer this, we @TAMU partnered with @Topaz and scholars from @Stanford, @Caltech, @UTAustin, @Snap, @ucmerced, @CUBoulder to develop the 𝘄𝗼𝗿𝗹𝗱’𝘀 𝗳𝗶𝗿𝘀𝘁 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗽𝗵𝗼𝘁𝗼 𝗿𝗲𝘀𝘁𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝘀𝘆𝘀𝘁𝗲𝗺.

Our system brings together over 𝟱𝟬 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗲𝗱 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹𝘀 — for denoising, deblurring, upscaling, face recovery, detail enhancement, and more.

🔬 It diagnoses the input image.
🦾 It plans and executes an action graph (just like a human editor).
☑️ After each step, it evaluates the output and adapts the plan if needed.

The results are phenomenal — as you’ll see in the video.

We believe democratizing professional photography will empower anyone to create images suitable for professional use cases. And because we see this as a responsibility, we are 𝗳𝘂𝗹𝗹𝘆 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 — to accelerate progress in agentic photo restoration and support the broader community.

👉 𝗖𝗵𝗲𝗰𝗸 𝗼𝘂𝘁 𝘁𝗵𝗲 𝗰𝗼𝗱𝗲: github.com/taco-group/4KA…
📄 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝘄𝗲𝗯𝗽𝗮𝗴𝗲: 4kagent.github.io

𝗜'𝗺 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿𝘄𝗮𝗿𝗱 𝘁𝗼 𝘀𝗲𝗲𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗯𝘂𝗶𝗹𝗱 𝘂𝘀𝗶𝗻𝗴 𝗼𝘂𝗿 𝗼𝗽𝗲𝗻–𝘀𝗼𝘂𝗿𝗰𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗻𝗱 𝘁𝗼 𝗿𝗲𝘃𝗶𝗲𝘄𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗱𝗲𝗺𝗼 𝗮𝗻𝗱 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸!

For folks working on #ICLR2027 rebuttals, you can check your rankings here:
songjhpku.github.io/ICLR2027-stati…

Can a frontier agent recursively improve the way it works?
We built Flex-RSI to measure exactly that: recursive self-improvement of frontier agents.
Check out more details below👇

Scaling title length leads to acceptance

如果你听信这个，17岁高中毕业就灵活就业，期待在十八线城市挂个vpn冲浪然后vibe coding几个github项目，就被远在旧金山的oai、a\挖到美国来工作，那这辈子有了