
Research @MistralAI | Previously @UCL_DARK
London
Joined June 2024
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🚀Scale a 1.6M-param transformer to one of today's strongest models, GPT-5.4, and it plans... 4 steps further.
In our latest work, we measure how many steps of latent planning LLMs can discover and execute without chain-of-thought and find a persistent depth ceiling that resists scale. 🧵👇
Yi Xu retweeted
This was accepted to COLM 2026 🥳
A striking limitation of SotA LLMs in discovering a latent planning strategy in an almost trivial graph-search task
Check out the paper ⤵️
Yi Xu retweeted
🚀 LLM from Trainee to Trainer.
No manual environment redesign.
No guessing where the model still struggles. 🤔
Let the model diagnose its own failures, and design the next training environment by itself. 🧠
We propose LLM-as-Environment Engineer, a new framework where LLMs not only learn in environments, but also learn to engineer the environments that teach them better. 🌍✨
The trainee becomes the trainer.
And training becomes self-improving. 🚀
Yi Xu retweeted
Happy to share that our paper Visual Planning has been selected as Oral for ICLR 2026 @iclr_conf 🥳🥳 #ICLR2026
📘Full attention visualizations, error breakdowns, training dynamics, and ablations here!
📄Read the paper: arxiv.org/abs/2604.06427
Huge thanks to @philippjettkant and @LauraRuis for the incredible collaboration. It was an absolute joy working together!
Yi Xu retweeted
Take a pause with textual CoT.
🧠✨ What if visual reasoning emerged from videos?
Video models aren’t just generators.
They can be generalizable, scalable reasoners. 🧵👇
Scaling! Scaling Test-Time Compute!
More Frames = More Thinking Budget = Better Planning!
Yi Xu retweeted
Self-Evolving AI Agents are about to blow up 🚀🔥
New Survey Alert 🚨
From static LLMs ➡️ lifelong, adaptive agents 🌱🤖
A Comprehensive Survey of Self-Evolving AI Agents... — your roadmap to the future of AI that learns & evolves after deployment! 💡
arxiv.org/pdf/2508.07407
Yi Xu retweeted
LLMs can be programmed by backprop 🔎
In our new preprint, we show they can act as fuzzy program interpreters and databases. After being ‘programmed’ with next-token prediction, they can retrieve, evaluate, and even *compose* programs at test time, without seeing I/O examples.
Yi Xu retweeted
Automating Multi-Agent Design:
🧩Multi-agent systems aren’t just about throwing more LLM agents together.
🛠️They require mastering the subtle art of prompting and agent orchestration.
Introducing MASS🚀- Our new agent optimization framework for better prompts and topologies!
🚀Let’s Think Only with Images.
No language and No verbal thought.🤔
Let’s think through a sequence of images💭, like how humans picture steps in their minds🎨.
We propose Visual Planning, a novel reasoning paradigm that enables models to reason purely through images.
📘 Want to know more?
📄 Read the paper: arxiv.org/abs/2505.11409
⭐️Star the repo: github.com/yix8/VisualPlanni…
Huge appreciation to @li_chengzu, @hanzhou032, and @wanxingchen_, @caiqizh, @annalkorhonen, @licwu for their incredible support and collaboration. It’s been truly rewarding to work together!











