Adam Yang @adam_x_yang
AI Scientist @MistralAI | Prev: @AmazonScience @Spotify @Huawei @BristolUni @imperialcollege @UniofOxford linkedin.com/in/adam-xinyu-… Joined March 2019-
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Introducing 20+ connectors powered by MCP and a fully controllable Memory in Le Chat—making it one of the most connected and relevant AI assistants for enterprises and consumers. Why switch to Le Chat? A 🧵
Mistral Medium 3.1 just landed on @lmarena_ai leaderboard—punching way above its weight! 🏆 #1 in English (no Style Control) 🏆 2nd overall (no Style Control) 🏆 Top 3 in Coding & Long Queries 🏆 8th overall Small model. Big impact. Try it now on Le Chat and the API!
Super exciting that my former student @edward_milsom is starting his lab at the University of Bath. Ed has led super-fundamental work on representation learning and learning dynamics. And he’s great fun to work with, so I definitely recommend collaborating!
Super exciting that my former student @edward_milsom is starting his lab at the University of Bath. Ed has led super-fundamental work on representation learning and learning dynamics. And he’s great fun to work with, so I definitely recommend collaborating!
🔎 LLM alignment techniques can enhance query expansion by eliminating the need for multiple generations followed by re-ranking/filtering steps. Check out this work led by @adam_x_yang during his internship with us at @SpotifyResearch w. @enricopalumbo91 and Hugues Bouchard⬇️
(1/4)🚨 Introducing Goedel-Prover V2 🚨 🔥🔥🔥 The strongest open-source theorem prover to date. 🥇 #1 on PutnamBench: Solves 64 problems—with far less compute. 🧠 New SOTA on MiniF2F: * 32B model hits 90.4% at Pass@32, beating DeepSeek-Prover-V2-671B’s 82.4%. * 8B > 671B: Our 8B…
Introducing powerful new features in Le Chat, making it more capable and more fun!
Introducing Mistral Small 3.2, a small update to Mistral Small 3.1 to improve: - Instruction following: Small 3.2 is better at following precise instructions - Repetition errors: Small 3.2 produces less infinite generations or repetitive answers - Function calling: Small…
Mixture-of-experts layers are a popular way to exploit conditional computation for Transformers. Recently, methods like DeepMind's mixture-of-depths have applied the same principles to skip entire layers based on the input token. But not all layers are created equal! 1/7
Is it possible to _derive_ an attention scheme with effective zero-shot generalisation? The answer turns out to be yes! To achieve this, we began by thinking about desirable properties for attention over long contexts, and we distilled 2 key conditions:
🚀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.
JSAEs got accepted at ICML! And we've got some exciting new qualitative results, stay tuned for a revision
JSAEs got accepted at ICML! And we've got some exciting new qualitative results, stay tuned for a revision
Our position paper on LLM eval error bars has just been accepted to ICML 2025 as a spotlight poster!
Our position paper on LLM eval error bars has just been accepted to ICML 2025 as a spotlight poster!
Happy to announce that my lab has four papers accepted at ICML, including one spotlight:
Introducing Le Chat Enterprise, the most customizable and secure agent-powered AI assistant for businesses, making AI a real leverage for competitiveness. - Integration with your company knowledge (starting with Gmail, Google Drive, Sharepoint…) - Ability to add frequently used…
Introducing Mistral Medium 3: our new multimodal model offering SOTA performance at 8X lower cost. - A new class of models that balances performance, cost, and deployability. - High performance in coding and function-calling. - Full enterprise capabilities, including hybrid or…
Our paper "Function-Space Learning Rates" is on arXiv! We give an efficient way to estimate the magnitude of changes to NN outputs caused by a particular weight update. We analyse optimiser dynamics in function space, and enable hyperparameter transfer with our scheme FLeRM! 🧵👇
Introducing the all new Le Chat: your ultimate AI sidekick for life and work! Now live on web and mobile!
I wrote a short note on why Bayesian neural networks are falling out-of-use with modern foundation models: because training for a single epoch on large datasets implicitly optimises the same objective as Bayes: laurencea.github.io/laurencea/dont…
After an incredible journey, I’ve finished my study as PhD student at UCL and am stepping into a new chapter as an Assistant Professor at the University of Bristol. From an uncertain undergrad to overcoming countless challenges along the way of research, there were many days…
🧵New research on Direct Alignment Algorithms for LLMs: 1️⃣ Higher likelihood for better completions & larger likelihood gaps ≠ better performance 2️⃣ Slightly lower likelihood improves diversity & generalisation 3️⃣ Identified 2 key indicators for likelihood over-optimisation
Md sayfullah haidar @sovon_haidar
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Lieqir @Lieqir942
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Nikhil Raghuraman @nikraghuraman
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Aloisia @73x6P7fFG4Pu0
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Vanessa @9EST751exrxj8
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Elodie @Kerdu86611
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Donnie @vibedonnie
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Tung Nguyen @tungnd_13
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Yulong Chen @Yulongchen1010
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Daniel Paleka @dpaleka
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Mingyu_Jin19 @fnruji316625
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Jiawei Zhao @jiawzhao
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DeepEval @deepeval
507 Followers 2 Following The Open-Source LLM Evaluation Framework – created and maintained by @confident_ai GitHub: https://t.co/kuvhlNRRdD
Yong Lin @Yong18850571
747 Followers 219 Following Postdoc Fellow @PrincetonPLI @Princeton. Co-leading the Goedel-Prover project. Apple AI/ML PhD Fellow 2023.
Gustavo Penha @_Guz_
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Crystal @crystalsssup
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Kevin Lu @_kevinlu
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Deedy @deedydas
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Kilo Code @Kilo_Code
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Jiayi Geng @JiayiiGeng
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Ziyu Yao @ZiyuYao
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Yifei Zhou @YifeiZhou02
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Chris Gorgolewski @chrisgorgo
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