Lightnews — Scholar-powered news

Reposted by Noga Zaslavsky

Randall Munroe @xkcd.com · Aug 12

Comic. [long message with unreadable text that includes lots of punctuation marks like semi colons and em dashes as well as citations.] Highlighted line at the bottom zoomed in reads: Not ChatGPT output—I’m just like this. [caption] I’ve had to start adding this disclaimer to my messages.

Noga Zaslavsky @nogazs.bsky.social · Aug 9

If you've reached so far and find this research exciting: my lab is recruiting a postdoc and PhD students!

➡️Postdoc applications: apply.interfolio.com/170656

➡️PhD applications: as.nyu.edu/psychology/g...

10/10

1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

Taken together, these studies further support the hypothesis that efficient compression is a fundamental principle underlying language, cognition, and intelligence more generally!

9/n

1 3

Noga Zaslavsky @nogazs.bsky.social · Aug 9

This further supports the generality of the IB principle and its applicability across the lexicon, and shows that action abstractions in language may be highly efficient

escholarship.org/uc/item/48w0...
w/ Thomas Langlois @rplevy.bsky.social @nidhise.bsky.social

8/n

Efficient compression in locomotion verbs across languages

Author(s): Langlois, Thomas A; Levy, Roger; Seethapathi, Nidhi; Zaslavsky, Noga | Abstract: Converging evidence suggests that languages are shaped by a drive for efficient communication. In particular...

escholarship.org

1 1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

We test this by considering a cross-linguistic dataset of locomotion naming 🏃‍♀️💃🚶
We find that even in this challenging dynamical multi-modal domain, systems of semantic categories across languages are significantly efficient

7/n

1 1 2

Noga Zaslavsky @nogazs.bsky.social · Aug 9

3️⃣ Our evidence supporting the IB framework for semantics has so far been based on static inputs like adjectives (e.g., color), nouns (e.g., objects), or function words (e.g., pronouns). Can this theory also apply to action verbs, referring to dynamic multi-modal inputs?

6/n

1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

This suggests that bilinguals must satisfy additional constraints while operating under the same pressure for efficiency as monolinguals

escholarship.org/uc/item/4128...
w/ Maya Taliaferro, Nathaniel Imel, Esti Blanco-Elorrieta

5/n

Bilinguals exhibit semantic convergence while maintaining near-optimal efficiency

Author(s): Taliaferro, Maya; Imel, Nathaniel; Blanco-Elorrieta, Esti; Zaslavsky, Noga | Abstract: Systems of semantic categories vary across languages, but this variation appears to be constrained by ...

escholarship.org

1 1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

2️⃣ Bilinguals employ two different category systems, but in practice they converge on systems that differ from monolinguals. Is this a sign bilinguals depart from efficiency to satisfy other (e.g., learnability) constraints? No, bilinguals still maintain optimality!

4/n

1 1 1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

individual learners seem to have an inductive bias toward maintaining optimally compressed representations, even without an explicit need to communicate

escholarship.org/uc/item/63d7...
w/ Nathaniel Imel, Jennifer Culbertson, @simonkirby.bsky.social

3/n

Iterated language learning is shaped by a drive for optimizing lossy compression

Author(s): Imel, Nathaniel; Culbertson, Jennifer; Kirby, Simon; Zaslavsky, Noga | Abstract: It has recently been theorized that languages evolve under pressure to attain near-optimal lossy compression...

escholarship.org

1 2

Noga Zaslavsky @nogazs.bsky.social · Aug 9

1️⃣ We've previously shown converging evidence that semantic categories across languages achieve near-optimal compression via the Information-Bottleneck principle. But how do languages become near-optimal?
By revisiting human iterated language learning data, we find that

2/n

1

Noga Zaslavsky @nogazs.bsky.social · Aug 9

If you missed us at #cogsci2025, my lab presented 3 new studies showing how efficient (lossy) compression shapes individual learners, bilinguals, and action abstractions in language, further demonstrating the extraordinary applicability of this principle to human cognition! 🧵

1/n

1 13 29

Noga Zaslavsky @nogazs.bsky.social · Jul 22

w/ @alisongopnik.bsky.social @norijacoby.bsky.social

1

Noga Zaslavsky @nogazs.bsky.social · Jul 22

Super excited to have the #InfoCog workshop this year at #CogSci2025! Join us in SF for an exciting lineup of speakers and panelists, and check out the workshop's website for more info and detailed scheduled
sites.google.com/view/infocog...

1 7 26

Reposted by Noga Zaslavsky

Cognitive Science Society @cogscisociety.bsky.social · Jul 16

#Workshop at #CogSci2025
Information Theory and Cognitive Science

🗓️ Wednesday, July 30
📍 Pacifica C - 8:30-10:00
🗣️ Noga Zaslavsky, Thomas A Langlois, Nathaniel Imel, Clara Meister, Eleonora Gualdoni, and Daniel Polani
🧑‍💻 underline.io/events/489/s...

Promotional image for a #CogSci2025 workshop titled “Information Theory and Cognitive Science.” Organized and presented by Noga Zaslavsky, Thomas A Langlois, Nathaniel Imel, Clara Meister, Eleonora Gualdoni, and Daniel Polani. Scheduled for July 30 at 8:30 AM in room Pacifica C. The top of the image features the conference theme, “Theories of the Past / Theories of the Future,” and the dates: July 30–August 2 in San Francisco.

1 1 4

Noga Zaslavsky @nogazs.bsky.social · Jul 21

📣 I'm looking for a postdoc to join my lab at NYU! Come work with me on a principled, theory-driven approach to studying language, learning, and reasoning, in humans and AI agents.
Apply here: apply.interfolio.com/170656
And come chat with me at #CogSci2025 if interested!

1 20 46

Reposted by Noga Zaslavsky

Centre for Language Evolution @uoe-cle.bsky.social · Jul 17

Nathaniel Imel, Jennifer Culbertson, @simonkirby.bsky.social & @nogazs.bsky.social:
Iterated language learning is shaped by a drive for optimizing lossy compression (Talks 37: Language and Computation 3, 1 August @ 16:22; blurb below) (2/)

1 1 1

Noga Zaslavsky @nogazs.bsky.social · Jun 6

This month I'm celebrating a decade (!!) since my first paper was published, which now has over 2,000 citations 🥹

"Deep learning and the information bottleneck principle" with the late, great Tali Tishby
ieeexplore.ieee.org/document/713...

Deep learning and the information bottleneck principle

Deep Neural Networks (DNNs) are analyzed via the theoretical framework of the information bottleneck (IB) principle. We first show that any DNN can be quantified by the mutual information between the ...

ieeexplore.ieee.org

1 14

Reposted by Noga Zaslavsky

Sydney Levine @sydneylevine.bsky.social · Jun 6

🔆 I'm hiring! 🔆

There are two open positions:

1. Summer research position (best for master's or graduate student); focus on computational social cognition.
2. Postdoc (currently interviewing!); focus on computational social cognition and AI safety.

sites.google.com/corp/site/sy...

Sydney Levine - Open Positions

Summer Research Position I am seeking a part-time or full-time researcher for the summer (starting asap) to bring a project to completion. The project asks the question: do people around the world u...

sites.google.com

1 24 33

Reposted by Noga Zaslavsky

Grace Lindsay @neurograce.bsky.social · May 10

Because we must build good things while we scream about the bad, I have started a "Data for Good" team @data-for-good-team.bsky.social that partners with organizations needing short-term data science help. We have three projects ongoing & will add more as our capacity grows.
data-for-good-team.org

8 68 150

Noga Zaslavsky @nogazs.bsky.social · Apr 24

Excited to share our new paper "Towards Human-Like Emergent Communication via Utility, Informativeness, and Complexity"
direct.mit.edu/opmi/article...
@rplevy.bsky.social

And looking forward to speaking about this line of work tomorrow at @nyudatascience.bsky.social!

Towards Human-Like Emergent Communication via Utility, Informativeness, and Complexity

Abstract. Two prominent, yet contrasting, theoretical views are available to characterize the underlying drivers of language evolution: on the one hand, task-specific utility maximization; on the othe...

direct.mit.edu

5 33

Reposted by Noga Zaslavsky

Yoshua Bengio @yoshuabengio.bsky.social · Mar 5

Congratulations to Rich Sutton and Andrew Barto on receiving the Turing Award in recognition of their significant contributions to ML. I also stand with them: Releasing models to the public without the right technical and societal safeguards is irresponsible.
www.ft.com/content/d8f8...

Turing Award winners warn over unsafe deployment of AI models

Two pioneers of reinforcement learning have won the $1mn prize from the Association for Computing Machinery

www.ft.com

25 120

Reposted by Noga Zaslavsky

Andrew Lampinen @lampinen.bsky.social · Feb 28

New preprint! In arxiv.org/abs/2502.20349 “Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior” we synthesize AI & cognitive science works to a perspective on seeking generalizable understanding of cognition. Thread:

Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior

Artificial Intelligence increasingly pursues large, complex models that perform many tasks within increasingly realistic domains. How, if at all, should these developments in AI influence cognitive sc...

arxiv.org

1 20 78

Noga Zaslavsky @nogazs.bsky.social · Jan 14

hi @xuanalogue.bsky.social , thanks so much for creating this starter pack! I'd love to be added too 😀

1 1

Reposted by Noga Zaslavsky

Eghbal Hosseini @eghbal-hosseini.bsky.social · Dec 27

Why do diverse ANNs resemble brain representations? Check out our new paper with Colton Casto, @nogazs.bsky.social , Colin Conwell, Mark Richardson, & @evfedorenko.bsky.social on “Universality of representation in biological and artificial neural networks.” 🧠🤖
tinyurl.com/yckndmjt

Universality of representation in biological and artificial neural networks

Many artificial neural networks (ANNs) trained with ecologically plausible objectives on naturalistic data align with behavior and neural representations in biological systems. Here, we show that this...

tinyurl.com

2 28 110