Highly recommended positions within MSFT!
Our AI Interaction and Learning team at
@MSFTResearch
is hiring research interns for next summer!
We are looking for PhD students interested in LLM post-training for effective AI interactions, user collaboration, agents/model capabilities assessment etc.
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Stefan Bauer retweeted
We're releasing dense Argus-format annotations for >5,000 hours (290k episodes) of public robot data (ABC-130k, MolmoAct2 YAM, DROID, GM-100, ABC-Sim), labeled with GPT 6.1 Sol.
Per-hand subgoals and actions, plus outcomes, mistakes, recoveries and object-state changes 👇🧵
6D
Per-hand subgoals and actions, plus outcomes, mistakes, recoveries and object-state changes 👇🧵
6D
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Stefan Bauer retweeted
NYU Center for Data Science is hiring Faculty Fellows! Apply by Nov 24 apply.interfolio.com/193498
CDS is hiring Faculty Fellows for fall 2027!
Two-year appointments with independent research, research and travel funds, and one course to teach per year.
Apply by November 24 for full consideration: apply.interfolio.com/193498
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Stefan Bauer retweeted
This project started with a literature search on "growing" work in modern vision pipelines, and I was surprised that there was not much, although there have been more recent works in language. Since I started my PhD by working on vision (object-centric?!) I was interested.
Excited to share “Growing to See”: growing SSL vision models provide better representations with up to 25% fewer FLOPs!
Co-led with @KaplFer.
With @Google’s Paradigms of Intelligence team (@kaitlinmaile & @oswaldjoh), @andrea_dittadi, Karl H. Johansson & @stefanAbauer.
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Stefan Bauer retweeted
Excited to share “Growing to See”: growing SSL vision models provide better representations with up to 25% fewer FLOPs!
Co-led with @KaplFer.
With @Google’s Paradigms of Intelligence team (@kaitlinmaile & @oswaldjoh), @andrea_dittadi, Karl H. Johansson & @stefanAbauer.
1/13
Co-led with @KaplFer.
With @Google’s Paradigms of Intelligence team (@kaitlinmaile & @oswaldjoh), @andrea_dittadi, Karl H. Johansson & @stefanAbauer.
1/13
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Stefan Bauer retweeted
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One-step generation is advancing fast: from flow maps to drifting models.
But how do we train a one-step sampler without target samples? 🤔
Introducing OSIS: “Amortised Inference through One-Step Implicit Sampling”.
Work co-led with @ktamogashev, as part of an ran Carter, @shchoi55, @stefanAbauer and Esmeralda S. Whitammer! 🙌
📄 arxiv.org/abs/2610.12679
More details about the method 🧵👇
One-step generation is advancing fast: from flow maps to drifting models.
But how do we train a one-step sampler without target samples? 🤔
Introducing OSIS: “Amortised Inference through One-Step Implicit Sampling”.
Work co-led with @ktamogashev, as part of an ran Carter, @shchoi55, @stefanAbauer and Esmeralda S. Whitammer! 🙌
📄 arxiv.org/abs/2610.12679
More details about the method 🧵👇
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Stefan Bauer retweeted
🆕 Very happy to share:
“One for All, All for One: Coordinated Multi-Agent Diffusion Steering via Stochastic Optimal Control”
Work co-led with top-notch collaborators @BarbanoRiccardo and Runchang Li 🤝
We show how to teach pretrained diffusion models to work together: , human motion, navigation and image components.
With frozen pretrained weights! ❄️
📄 Paper: arxiv.org/abs/2610.08595
Grateful to an incredible team: George Webber, Alexander Denker, Željko Kereta, @stefanAbauer, Francisco Vargas and Esmeralda S. Whitammer. 🙌
Idea, theory, and some examples below 🧵👇
“One for All, All for One: Coordinated Multi-Agent Diffusion Steering via Stochastic Optimal Control”
Work co-led with top-notch collaborators @BarbanoRiccardo and Runchang Li 🤝
We show how to teach pretrained diffusion models to work together: , human motion, navigation and image components.
With frozen pretrained weights! ❄️
📄 Paper: arxiv.org/abs/2610.08595
Grateful to an incredible team: George Webber, Alexander Denker, Željko Kereta, @stefanAbauer, Francisco Vargas and Esmeralda S. Whitammer. 🙌
Idea, theory, and some examples below 🧵👇
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Stefan Bauer retweeted
@fvderop Incredible spin. Takes real talent to take a rigorous & reasonable study (that should have been done before they built their big foundation models) & twist it to further their virtual cell nonsense propaganda.
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Stefan Bauer retweeted
Best possible model quality under fixed training compute, memory, and enable test time scaling under varying recurrence ?
We systematically study how model size, data, sparsity, and recurrent depth interact.
Loop Scaling Laws predict the frontier: how much effective capacity aturates, and how MoE sparsity raises that ceiling.
Work by @yanbei_c (follow her!)
arxiv.org/abs/2609.40316
We systematically study how model size, data, sparsity, and recurrent depth interact.
Loop Scaling Laws predict the frontier: how much effective capacity aturates, and how MoE sparsity raises that ceiling.
Work by @yanbei_c (follow her!)
arxiv.org/abs/2609.40316
Frontier models like GPT-6 are reportedly using looping. But here're the million-dollar questions on scaling: 🤔 Can adding more loops deliver gains indefinitely? And what happens when looping meets Mixture-of-Experts?
Check out our latest Loop Scaling Laws answering these! 👇
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Stefan Bauer retweeted
📣 Applications are open for the CIFAR Global Scholars program!
Develop and lead highly interdisciplinary research, expand your network and gain valuable leadership training.
🔗 Learn more and apply by November 4: cifar.ca/next-generatio…
Develop and lead highly interdisciplinary research, expand your network and gain valuable leadership training.
🔗 Learn more and apply by November 4: cifar.ca/next-generatio…
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Stefan Bauer retweeted
Thanks to the great feedback we received, we’ve made a few updates to the Foundations of Diffusion manuscript.
Summer isn’t quite over yet, still time to dive into diffusion! 😎🌴
arXiv: arxiv.org/abs/2512.05092
Summer isn’t quite over yet, still time to dive into diffusion! 😎🌴
arXiv: arxiv.org/abs/2512.05092
🚨 Looking for a fully self-contained intro to diffusion models that covers both continuous (images) and discrete (text, sequences) data?
🆕 We just released:
“Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction”
arxiv : arxiv.org/abs/2512.05092
S/o to @andrea_dittadi for his amazing support & guidance, and huge thanks to @TobiasHppe1, @k_neklyudov, @AlexanderTong7 and @stefanAbauer for their supervision! 🙌
One roadmap for all of diffusion. 🏎️💨
After a few failed posts, broken previews, and getting briefly flagged by X… the full thread's finally out 🤯🧵👇
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Stefan Bauer retweeted
reminder that "physically accurate" video model claims are only as good as the benchmark measuring them! 👩🔬
new Physics-IQ audit found >1/3 of prompts were ambiguous and ~30% of videos had artifacts inflating scores. after cleanup, model rankings changed meaningfully (τ=0.46)
vibes ≠ physics
new Physics-IQ audit found >1/3 of prompts were ambiguous and ~30% of videos had artifacts inflating scores. after cleanup, model rankings changed meaningfully (τ=0.46)
vibes ≠ physics
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Evaluations are the secret sauce of frontier labs and Anates is launching its first project in a collaboration with Deepmind. If you work on video models and or embodied intelligence check out their work! Congrats Tim and Carsten!
𝐂𝐚𝐧 𝐚 𝐯𝐢𝐝𝐞𝐨 𝐦𝐨𝐝𝐞𝐥 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐫𝐞𝐚𝐬𝐨𝐧 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐰𝐨𝐫𝐥𝐝, 𝐨𝐫 𝐢𝐬 𝐢𝐭 𝐣𝐮𝐬𝐭 𝐩𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐩𝐥𝐚𝐮𝐬𝐢𝐛𝐥𝐞-𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐦𝐨𝐭𝐢𝐨𝐧?
Today, we are excited to introduce 𝐏𝐡𝐲𝐬𝐢𝐜𝐬-𝐈𝐐 𝐕𝐞𝐫𝐢𝐟𝐢𝐞𝐝
(1/n)
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Stefan Bauer retweeted
𝐂𝐚𝐧 𝐚 𝐯𝐢𝐝𝐞𝐨 𝐦𝐨𝐝𝐞𝐥 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐫𝐞𝐚𝐬𝐨𝐧 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐰𝐨𝐫𝐥𝐝, 𝐨𝐫 𝐢𝐬 𝐢𝐭 𝐣𝐮𝐬𝐭 𝐩𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐩𝐥𝐚𝐮𝐬𝐢𝐛𝐥𝐞-𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐦𝐨𝐭𝐢𝐨𝐧?
Today, we are excited to introduce 𝐏𝐡𝐲𝐬𝐢𝐜𝐬-𝐈𝐐 𝐕𝐞𝐫𝐢𝐟𝐢𝐞𝐝
(1/n)
Today, we are excited to introduce 𝐏𝐡𝐲𝐬𝐢𝐜𝐬-𝐈𝐐 𝐕𝐞𝐫𝐢𝐟𝐢𝐞𝐝
(1/n)
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Stefan Bauer retweeted
AI started in canada with CIFAR, and AI continues here in canada with @CIFAR_News
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Stefan Bauer retweeted
I am moving to @ICComputing at @imperialcollege as an associate professor, where I will be expanding my lab!
I am looking for PhDs and postdocs to join me on my quest to build foundation models with adaptive tokenisation and memory (AToM FMs, funded by @ERC_Research)
I am looking for PhDs and postdocs to join me on my quest to build foundation models with adaptive tokenisation and memory (AToM FMs, funded by @ERC_Research)
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