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sineadwilliamson.bsky.social

@sineadwilliamson.bsky.social
68 followers 92 following 6 posts
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Gautam Kamath @gautamkamath.com · 03/12/2025
If you are a senior researcher at #NeurIPS2025 (i.e., roughly full professor level or later), and you're interested in moving to the University of Waterloo (best CS program in Canada) for a CERC (biggest chair position in Canada), email me. Discretion guaranteed.
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Reposted by @sineadwilliamson.bsky.social
Cheng Soon Ong @ml4x.bsky.social · 26/11/2025
If you like our @deisenroth.bsky.social #mathematics for #machinelearning textbook, and want a hard copy, Cambridge is providing a 30% discount for #NeurIPS2025. Of course you can buy other books, and also download the PDF from: mml-book.com www.cambridge.org/us/universit... Discount code: 107890
mml-book.com
Mathematics for Machine Learning
Companion webpage to the book “Mathematics for Machine Learning”. Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press.
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sineadwilliamson.bsky.social @sineadwilliamson.bsky.social · 07/11/2025
📢 We’re looking for a researcher in in cogsci, neuroscience, linguistics, or related disciplines to work with us at Apple Machine Learning Research! We're hiring for a one-year interdisciplinary AIML Resident to work on understanding reasoning and decision making in LLMs. 🧵
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Reposted by @sineadwilliamson.bsky.social
Marco Cuturi @marcocuturi.bsky.social · 05/11/2025
We have been working with Michal Klein on pushing a module to train *flow matching* models using JAX. This is shipped as part of our new release of the OTT-JAX toolbox (github.com/ott-jax/ott) The tutorial to do so is here: ott-jax.readthedocs.io/tutorials/ne...
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sineadwilliamson.bsky.social @sineadwilliamson.bsky.social · 02/10/2025
Really glad to have been a part of this super cool project... LLMs can verbalize more than just a single confidence number, and we can evaluate their ability to do so!
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Reposted by @sineadwilliamson.bsky.social
Michael Kirchhof @mkirchhof.bsky.social · 01/10/2025
Many treat uncertainty = a number. At Apple, we're rethinking this: LLMs should output strings that reveal all information of their internal distributions. We find that Reasoning, SFT, CoT can't do it - yet. To get there, we introduce the SelfReflect benchmark. arxiv.org/pdf/2505.20295
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Reposted by @sineadwilliamson.bsky.social
Shubhendu Trivedi @shubhendu.bsky.social · 01/09/2025
Natural idea. Looks like a nice paper too. arxiv.org/abs/2508.21184
arxiv.org
BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design
We propose a general-purpose approach for improving the ability of Large Language Models (LLMs) to intelligently and adaptively gather information from a user or other external source using the framew...
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Reposted by @sineadwilliamson.bsky.social
Maureen de Seyssel @maureendeseyssel.bsky.social · 27/05/2025
Now that @interspeech.bsky.social registration is open, time for some shameless promo! Sign-up and join our Interspeech tutorial: Speech Technology Meets Early Language Acquisition: How Interdisciplinary Efforts Benefit Both Fields. 🗣️👶 www.interspeech2025.org/tutorials ⬇️ (1/2)
interspeech2025.org
https://www.interspeech2025.org/tutorials
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