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Pietro Michiardi @michiardi.bsky.social · 27/01/2026

💥 Happy to share that our paper “Information Estimation with Discrete Diffusion” has been accepted to ICLR 2026! 💥 📄 Paper (OpenReview): lnkd.in/eayzTJQb Congratulation to our Ph.D. student Alberto Foresti, that my colleague Prof. Giulio Franzese and I jointly supervise!

lnkd.in

This link will take you to a page that’s not on LinkedIn

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Fernando Rosas @frosas.bsky.social · 15/01/2026

Looking forward to participate in this workshop on high-order interactions and multivariate information theory: mithic2026.github.io

mithic2026.github.io

MITHIC 2026

Unveiling Complex Interactions

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Griffiths Computational Cognitive Science Lab @cocoscilab.bsky.social · 18/12/2025

Excited to announce a new book telling the story of mathematical approaches to studying the mind, from the origins of cognitive science to modern AI! The Laws of Thought will be published in February and is available for pre-order now.

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Sam Gershman @gershbrain.bsky.social · 09/01/2026

With some trepidation, I'm putting this out into the world: gershmanlab.com/textbook.html It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class. My hope is that this will be a living document, continuously improved as I get feedback.

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Sebastian Raschka (rasbt) @rasbt.bsky.social · 30/12/2025

Uploaded my State of LLMs 2025 report for this year: magazine.sebastianraschka.com/p/state-of-l... I planned to just write a brief overview, but yeah, it was an eventful year so it was impossible to keep it below 7000 words :D.

magazine.sebastianraschka.com

The State Of LLMs 2025: Progress, Progress, and Predictions

A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

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Sebastian Raschka (rasbt) @rasbt.bsky.social · 13/12/2025

Just updated the Big LLM Architecture Comparison article... ...it grew quite a bit since the initial version in July 2025, more than doubled! magazine.sebastianraschka.com/p/the-big-ll...

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Vertaix (AI&Science Lab at Princeton University) @vertaix.bsky.social · 04/06/2025

Our paper introducing Alternators has been accepted at TMLR. Alternators are a new class of generative models that outperform state-space models, such as Mambas, and diffusion models such as ScoreGrad. Check it out! Paper: arxiv.org/abs/2405.11848 Code: github.com/vertaix/Alternators #MLSky #Vertaix

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Raphaël Troncy @rtroncy.bsky.social · 22/04/2025

📢A unique fully funded three-years PhD position is open at POLITO and EURECOM. Title: Enhancing Educational Storytelling with Human-Centered AI in the LLM Era Application deadline: April 28, 2025 Details: www.linkedin.com/feed/update/...

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Sander Dieleman @sedielem.bsky.social · 14/04/2025

Amazing interview with Yang Song, one of the key researchers we have to thank for diffusion models. The most important lesson: be fearless! The community's view on score matching was quite pessimistic at the time, he went against the grain and made it work at scale! www.youtube.com/watch?v=ud6z...

youtube.com

History of Diffusion - Yang Song

YouTube video by Bain Capital Ventures

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Sebastian Raschka (rasbt) @rasbt.bsky.social · 08/03/2025

I just shared a new article, "The State of Reasoning Models", where I am exploring 12 new research articles on improving the reasoning capabilities of LLMs (all published after the release of DeepSeek R1): magazine.sebastianraschka.com/p/state-of-l... Happy reading!

magazine.sebastianraschka.com

The State of LLM Reasoning Models

Part 1: Inference-Time Compute Scaling Methods

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Pietro Michiardi @michiardi.bsky.social · 06/02/2025

Happy to share that our paper, "Information Theoretic Text-to-Image Alignment," has been accepted at ICLR 2025! 🚀 Kudos to the team: Chao Wang, the PhD student leading this work, Alessandro Finamore, Max Gallo, and Giulio Franzese. arxiv.org/abs/2405.20759

arxiv.org

Information Theoretic Text-to-Image Alignment

Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a laborious trial-and-error ...

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Christian A. Naesseth @canaesseth.bsky.social · 05/02/2025

Really excited about this! We note a connection between diffusion/flow models and neural/latent SDEs. We show how to use this for simulation-free learning of fully flexible SDEs. We refer to this as SDE Matching and show speed improvements of several orders of magnitude. arxiv.org/abs/2502.02472

arxiv.org

SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations

The Latent Stochastic Differential Equation (SDE) is a powerful tool for time series and sequence modeling. However, training Latent SDEs typically relies on adjoint sensitivity methods, which depend ...

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Valérie Castin @vcastin.bsky.social · 31/01/2025

How do tokens evolve as they are processed by a deep Transformer? With José A. Carrillo, @gabrielpeyre.bsky.social and @pierreablin.bsky.social, we tackle this in our new preprint: A Unified Perspective on the Dynamics of Deep Transformers arxiv.org/abs/2501.18322 ML and PDE lovers, check it out!

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Pierre-Alexandre Mattei @pamattei.bsky.social · 10/01/2025

We’re organizing once again the Gznerative Modeling Summer school this spring on the Côte d’Azur, merged for the occasion with SFdS’s Statlearn! Applications are open!

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Jes Frellsen @jesfrellsen.bsky.social · 10/01/2025

Excited about 🎓 Generative Modeling Summer School / Statlearn 🗓️ Mar 31 - Apr 4, 2025, France ℹ️ gemss.ai 🎟️ Deadline: Jan 27, 2025 🧑‍🏫 Yingzhen Li, @stephanmandt.bsky.social, Aude Sportisse, Anna Korba, @glouppe.bsky.social, @jesfrellsen.bsky.social, @pamattei.bsky.social, @jmtomczak.bsky.social, TBA

gemss.ai

Generative Modeling Summer School (GeMSS)

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Arnaud Doucet @arnauddoucet.bsky.social · 15/12/2024

The slides of my NeurIPS lecture "From Diffusion Models to Schrödinger Bridges - Generative Modeling meets Optimal Transport" can be found here drive.google.com/file/d/1eLa3...

drive.google.com

BreimanLectureNeurIPS2024_Doucet.pdf

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Raphaël Troncy @rtroncy.bsky.social · 16/12/2024

Meet EULER (EURECOM Language Model for Education and Research) and our new #Socratic LLM for AI-Driven Education, eurecom-blog.medium.com/eurecoms-soc... Model available @huggingface.bsky.social and @ollama.bsky.social #LLM #RAG #EduTech

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Sasha Rush @srushnlp.bsky.social · 21/11/2024

Discrete diffusion has become a very hot topic again this year. Dozens of interesting ICLR submissions and some exciting attempts at scaling. Here's a bibliography on the topic from the Kuleshov group (my open office neighbors). github.com/kuleshov-gro...

github.com

GitHub - kuleshov-group/awesome-discrete-diffusion-models: A curated list for awesome discrete diffusion models resources.

A curated list for awesome discrete diffusion models resources. - kuleshov-group/awesome-discrete-diffusion-models

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Blake Richards @tyrellturing.bsky.social · 21/11/2024

1/ I work in #NeuroAI, a growing field of research, which many people have only the haziest conception of... As way of introduction to this research approach, I'll provide here a very short thread outlining the definition of the field I gave recently at our BRAIN NeuroAI workshop at the NIH. 🧠📈

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Roberto Toro @r3rt0.bsky.social · 21/11/2024

🧠 Come work with us! In addition to our postdoc position on modelling, our lab at @institutpasteur.bsky.social we also seek a postdoc to help us create the most complete open atlas of brain folding development! This is part of our ERC Synergy project Unfold (unfold-lab.github.io). Join us! (1/10)

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Motonobu Kanagawa @motonobu-kanagawa.bsky.social · 17/11/2024

We are organising the First International Conference on Probabilistic Numerics (ProbNum 2025) at EURECOM in southern France in Sep 2025. Topics: AI, ML, Stat, Sim, and Numerics. Reposts very much appreciated! probnum25.github.io

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