Yi Xu (@_yixu) header
Yi Xu (@_yixu) profile picture

Research @MistralAI | Previously @UCL_DARK

London
Joined June 2024
Pinned Tweet
🚀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. 🧵👇
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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 ⤵️
🚀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. 🧵👇
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🚀 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. 🚀
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Happy to share that our paper Visual Planning has been selected as Oral for ICLR 2026 @iclr_conf 🥳🥳 #ICLR2026
🚀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.
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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!
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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
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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.
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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!
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🚀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.
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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!
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