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.

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

📢 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. 🧵

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...

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!

Michael Kirchhof@mkirchhof.bsky.social · 10mo ago

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

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

Natural idea. Looks like a nice paper too. arxiv.org/abs/2508.21184

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...

arxiv.org

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)