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Reposted by Samuel Lippl

UniReps @unireps.bsky.social · 25/09/2026

NeurIPS decisions not quite what you hoped for? We look forward to having you at UniReps! December 12th, 2026 in Paris. Submission deadline October 4th AOE. Call for papers: unireps.org/2026/call-fo... Submit here: openreview.net/group?id=Uni...

unireps.org

Call For Papers | UniReps Workshop

Unifying Representations in Neural Models

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Reposted by Samuel Lippl

UniReps @unireps.bsky.social · 04/09/2026

📣 Call for Papers: UniReps Workshop in Paris! We invite work exploring why, when, and how distinct learning processes yield similar representations across AI, neuroscience & cognitive science. 📅 Deadline: Oct 4 (AoE) unireps.org/2026/call-fo...

unireps.org

Call For Papers | UniReps Workshop

Unifying Representations in Neural Models

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Reposted by Samuel Lippl

UniReps @unireps.bsky.social · 14/08/2026

🚀 UniReps 4th Edition is coming! 🌍✨ We’re aiming to host a UniReps satellite event around NeurIPS 2026 in Paris! Join us to connect, collaborate, and shape the future of representation learning. Your voice matters! Let us know which dates work best for you. docs.google.com/forms/d/e/1F...

docs.google.com

Call for Partecipation - UniReps 4th Edition

We’re excited to announce that we’re organizing the 4th edition of UniReps as a satellite event in Paris and would love your help in choosing the best date for the community. Your feedback will ensure...

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Samuel Lippl @sflippl.bsky.social · 03/08/2026

Really excited about this project! If you want to chat about repulsion and representational changes in hippocampus, come by our poster at #CCN2026 tomorrow at 9:30!

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Reposted by Samuel Lippl

Anna Schapiro @annaschapiro.bsky.social · 01/08/2026

Here's where to find the Penn Computational Cognitive Neuroscience Lab at Cognitive Computational Neuroscience next week! See you in NYC!

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Samuel Lippl @sflippl.bsky.social · 11/07/2026

Excited to present this paper that was led by Luke today at the CompLearn workshop (2nd poster session, starting at 4). If you want to chat about how simple learning systems can learn relational rules but also memorize exceptions to those rules, come by!

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Samuel Lippl @sflippl.bsky.social · 08/07/2026

Excited to be presenting this paper tomorrow! If you want to hear more about this, please come to the poster session tomorrow at 2:30pm @icmlconf.bsky.social.

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Samuel Lippl @sflippl.bsky.social · 08/07/2026

Pretraining + fine-tuning powers modern ML, but we lack a theoretical understanding of how pretraining actually shapes downstream learning. In our new @icmlconf.bsky.social paper, we address this gap! 📅 July 9th, Poster #4502 Session 8! 🧵 arxiv.org/pdf/2602.20062

Diagram with "l-order" on the x-axis and "Pretraining dependence" on the y axis. The diagram highlights that only the upper right triangle is a possible region and highlights four distinct regimes: (I) a rich, pretraining independent regime, (II) a lazy, pretraining-dependent regime, (III) lazy, pretraining-independent regime, and (IV) a rich, pretraining dependent regime. Different initialization parameters move us between these regimes.

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