iiinova — where your digital self keeps evolving

Reposted by Mandana Samiei

Alireza Modirshanechi @modirshanechi.bsky.social · 15/08/2026

Excited to share that I'll be starting as a junior professor and Emmy Noether awardee at the University of Göttingen this October! 🥳 🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci: modirlab.github.io/open-positio... Please spread the word! 🙏

Information about Göttingen and equal opportunities

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Mandana Samiei @mandanas.bsky.social · 24/07/2026

Presenting our work today at #CogSci2026 🎉 Our findings reveal interesting similarities, and important differences, in how humans and modern AI systems explore causal structures. If you're at the conference, come by and say hello! Today 5:30–7:00pm Reasoning session, P3-L-104

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Blake Richards @tyrellturing.bsky.social · 07/07/2026

1/2) Please let's all remember that GWT is a theoy of access consciousness (what is available for verbal reasoning) and not phenomenal consciousness (subjective experience): philpapers.org/rec/BLOOAC Obviously, in this study access consciousness is literally what they test in the LLMs. #NeuroAI 🧪

philpapers.org

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Dongyan Lin @dongyanl1n.bsky.social · 19/06/2026

Check out our new work: how do humans and LLMs explore causal structures differently?

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Mandana Samiei @mandanas.bsky.social · 19/06/2026

We recently investigated how humans and AI reason through causal rules: arxiv.org/abs/2606.06464 Accepted at #CogSci2026. We gave adults and LLMs agency to actively experiment using a Blicket causal game, breaking down their process into the iterative loop shown in the following figure:

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Alison Gopnik @alisongopnik.bsky.social · 17/06/2026

Two new preprints from the lab, First up, causal exploration in humans and LLM's. arxiv.org Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?

arxiv.org

arXiv.org e-Print archive

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Mandana Samiei @mandanas.bsky.social · 17/06/2026

Very much looking forward to this!

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peterdoohan.bsky.social @peterdoohan.bsky.social · 11/06/2026

How do brains plan actions towards goals? To get at this question we studied mice navigating complex mazes as goals changed on every trial 🧵 Work with @thomasakam.bsky.social @behrenstimb.bsky.social @kristorpjensen.bsky.social now on BioRxiv: www.biorxiv.org/content/10.6...

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Blake Richards @tyrellturing.bsky.social · 03/06/2026

New perspective piece with @mandanas.bsky.social: We argue, based on LLMs and old connectionist theories, that schemas shouldn't be viewed as distinct from semantic or episodic memories. They're just one end of a detailed-to-abstract memory spectrum: www.cell.com/neuron/fullt... #NeuroAI 🧠📈 🧪

cell.com

The schema spectrum: Emergent structures and levels of abstraction in AI and the brain

Motivated by generative AI, Samiei et al. argue against classical models that treat schemas as distinct memory structures. Instead, they propose that schemas are merely a conceptual tool describing ho...

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Mandana Samiei @mandanas.bsky.social · 04/06/2026

Excited to see our perspective out today! We argue that schemas may not be fundamentally distinct from semantic and episodic memories, but instead lie along a spectrum of abstraction, from detailed episodic experiences to highly abstract knowledge. See more: doi.org/10.1016/j.ne...

doi.org

Redirecting

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Columbia University's Zuckerman Institute @zuckermanbrain.bsky.social · 19/03/2026

How can machines achieve the kind of flexible learning mastered by our brains? That’s what our own @neurokim.bsky.social is trying to find out! Learn more about ARNI’s work on natural and artificial intelligence: youtu.be/gM8YCaiAWrc?... #BrainAwarenessWeek

youtu.be

ARNI: Memory Driven Learning with Kim Stachenfeld

YouTube video by Columbia Engineering

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Claire Vernade @claireve.bsky.social · 18/02/2026

Check out the Call for Workshops at RLC this year. There is still nearly a month before the deadline, we are looking forward to your proposals!

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Andrew Lampinen @lampinen.bsky.social · 18/02/2026

What is the relationship between memorization and generalization in AI? Is there a fundamental tradeoff? In infinitefaculty.substack.com/p/memorizati... I’ve reviewed some of the evolving perspectives on memorization & generalization in machine learning, from classic perspectives through LLMs.

infinitefaculty.substack.com

Memorization vs. generalization in deep learning: implicit biases, benign overfitting, and more

Or: how I learned to stop worrying and love the memorization

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Rim Assouel @rassouel.bsky.social · 06/02/2026

Excited to share that our work on Visual Symbolic Mechanisms has been accepted to ICLR! 🌴🇧🇷

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Mandana Samiei @mandanas.bsky.social · 30/06/2025

Huge congratulations! Already looking forward to the breakthroughs you'll lead!

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Mandana Samiei @mandanas.bsky.social · 30/06/2025

Great deep dive into hierarchical reinforcement learning, essential reading for anyone exploring scalable, structured agents. Shoutout to the authors!

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Mandana Samiei @mandanas.bsky.social · 16/05/2025

Many LMs default to disjunctive inferences—even when given conjunctive evidence. Unlike children, LMs’ exploration is shaped by the underlying causal rule. Could promoting child-like curiosity help LMs reason more effectively about causality? More details: arxiv.org/abs/2505.09614

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Mandana Samiei @mandanas.bsky.social · 16/05/2025

A great collab with former labmates @agx-chen.bsky.social & @dongyanl1n.bsky.social. Interesting limitation in LMs: strong disjunctive bias leads to poor performance on conjunctive causal inference tasks. Mirrors adult human biases--possibly a byproduct of training data prior.

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Arna Ghosh @arnaghosh.bsky.social · 10/02/2025

Just over a week since I defended my 🤖+🧠PhD thesis, and the feeling is just sinking in. Extremely grateful to @tyrellturing.bsky.social for supporting me through this amazing journey! 🙏 Big thanks to all members of the LiNC lab, and colleagues at mcgill University and @mila-quebec.bsky.social. ❤️😁

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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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Thomas Kipf @tkipf.bsky.social · 19/12/2024

I gave a talk on Compositional World Models at NeurIPS last week 🌐 The recording is now online: neurips.cc/virtual/2024... (for registered attendees; starts at 6:06:00) Workshop: compositional-learning.github.io

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Joey Bose @joeybose.bsky.social · 18/12/2024

🔊 Super excited to announce the first ever Frontiers of Probabilistic Inference: Learning meets Sampling workshop at #ICLR2025 @iclr-conf.bsky.social! 🔗 website: sites.google.com/view/fpiwork... 🔥 Call for papers: sites.google.com/view/fpiwork... more details in thread below👇 🧵

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Blake Richards @tyrellturing.bsky.social · 04/12/2024

If you review for a #ML conference like @iclr-conf.bsky.social or @neuripsconf.bsky.social, YOU HAVE A RESPONSIBILITY TO REPLY TO THE AUTHORS. If the rebuttal doesn't address your concerns explain why. But giving a score of 2-3 then ghosting the authors is super rude. I say this as an AC. #MLSky

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Tim Rocktäschel @handle.invalid · 20/11/2024

Now that @jeffclune.bsky.social and @joelbot3000.bsky.social are here, time for an Open-Endedness starter pack. go.bsky.app/MdVxrtD

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

4/ I think the proper definition is that #NeuroAI is the realization of the original promise of cybernetics and connectionism! en.wikipedia.org/wiki/Cyberne... en.wikipedia.org/wiki/Connect... It is a general science of intelligence focussed on parallel distributed systems, control, and learning.

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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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Sam Gershman @gershbrain.bsky.social · 12/11/2024

I wish that I was able to convince the students in my class that the ultimate goal of science isn't accumulation of facts but the compression of facts into theories. Mel summarizes it well here: www.nature.com/articles/nn1... Unfortunately, I think this is a minority viewpoint within neuroscience.

nature.com

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