Publications | Noga Zaslavsky

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Optimal compression in human concept learning

Nathaniel Imel, Noga Zaslavsky. CogSci, 2024.

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Language use is only sparsely compositional: The case of English adjective-noun phrases in humans and large language models

Aalok Sathe, Evelina Fedorenko, Noga Zaslavsky. CogSci, 2024.

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Bridging semantics and pragmatics in information-theoretic emergent communication

Eleonora Gualdoni, Mycal Tucker, Roger P. Levy, Noga Zaslavsky. SCiL, 2024.

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Discreteness and systematicity emerge to facilitate communication in a continuous signal-meaning space

Alicia Chen, Matthias Hofer, Moshe Poliak, Roger P. Levy, and Noga Zaslavsky. EvoLang XV, 2024.

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Artificial neural network language models predict human brain responses to language even after a developmentally realistic amount of training

Eghbal A Hosseini, Martin Schrimpf, Yian Zhang, Samuel Bowman, Noga Zaslavsky, Evelina Fedorenko. Neurobiology of Language, 2024.

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Noisy Population Dynamics Lead to Efficiently Compressed Semantic Systems

Nathaniel Imel, Richard Futrell, Michael Franke, Noga Zaslavsky. InfoCog @ NeruIPS, 2023.

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Human-Guided Complexity-Controlled Abstractions

Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie Shah. NeurIPS, 2023.

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Teasing apart the representational spaces of ANN language models to discover key axes of model-to-brain alignment

Eghbal Hosseini, Noga Zaslavsky, Colton Casto, Evelina Fedorenko. CCN, 2023.

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Evidence for a language-independent conceptual representation of pronominal referents

Mora Maldonado, Noga Zaslavsky, Jennifer Culbertson. CogSci, 2023.

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Alignment of ANN Language Models with Humans After a Developmentally Realistic Amount of Training

Eghbal Hosseini, Martin Schrimpf, Yian Zhang, Samuel Bowman, Noga Zaslavsky, Evelina Fedorenko. COSYNE, 2023.

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Generalization and Translatability in Emergent Communication via Informational Constraints

Mycal Tucker, Roger Levy, Julie Shah, Noga Zaslavsky. InfoCog @ NeurIPS, 2022.

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Trading off Utility, Informativeness, and Complexity in Emergent Communication

Mycal Tucker, Julie Shah, Roger Levy, Noga Zaslavsky. NeurIPS, 2022.

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Beyond linear regression: mapping models in cognitive neuroscience should align with research goals

Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti, Noga Zaslavsky, Evelina Fedorenko, Leyla Isik. NBDT, 2022.

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Towards Human-Agent Communication via the Information Bottleneck Principle

Mycal Tucker, Julie Shah, Roger Levy, Noga Zaslavsky. RSS Workshop on Social Intelligence in Humans and Robots, 2022.

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Teasing apart models of pragmatics using optimal reference game design

Irene Zhou, Jennifer Hu, Roger Levy, Noga Zaslavsky. CogSci, 2022.

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The emergence of discrete and systematic communication in a continuous signal-meaning space

Alicia Chen, Matthias Hofer, Moshe Poliak, Roger Levy, Noga Zaslavsky. CogSci, 2022.

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The evolution of color naming reflects pressure for efficiency: Evidence from the recent past

Noga Zaslavsky*, Karee Garvin*, Charles Kemp, Naftali Tishby, Terry Regier. Journal of Language Evolution, 2022.

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The forms and meanings of grammatical markers support efficient communication

Francis Mollica, Geoffrey Bacon, Noga Zaslavsky, Yang Xu, Terry Regier, Charles Kemp. PNAS, 2021.

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Scalable pragmatic communication via self-supervision

Jennifer Hu, Roger Levy, Noga Zaslavsky. ICML Workshop on Self-Supervised Learning for Reasoning and Perception, 2021.

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Let's talk (efficiently) about us: Person systems achieve near-optimal compression

Noga Zaslavsky*, Mora Maldonado*, Jennifer Culbertson. CogSci, 2021.

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Empirical support for a Rate-Distortion account of pragmatic reasoning

Irene Zhou, Jennifer Hu, Roger P. Levy, Noga Zaslavsky. CogSci, 2021.

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Competition from novel features drives scalar inferences in reference games

Jennifer Hu, Noga Zaslavsky, Roger P. Levy. CogSci, 2021.

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Is it that simple? Linear mapping models in cognitive neuroscience

Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti, Noga Zaslavsky, Evelina Fedorenko, Leyla Isik. bioRxiv, 2021.

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Probing artificial neural networks: insights from neuroscience

Anna A. Ivanova, John Hewitt, Noga Zaslavsky. ICLR Brain2AI Workshop, 2021.

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Crosslinguistic patterns in person systems reflect efficient coding

Mora Maldonado*, Noga Zaslavsky*, Jennifer Culbertson. CUNY, 2021.

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A Rate–Distortion view of human pragmatic reasoning

Noga Zaslavsky, Jennifer Hu, Roger Levy. SCiL, 2021.

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Bayesian Approaches to Color Category Learning

Thomas Griffiths, Noga Zaslavsky. Encyclopedia of Color Science and Technology, 2021.

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Cloze Distillation: Improving Neural Language Models with Human Next-Word Prediction

Tiwalayo Eisape, Noga Zaslavsky, Roger Levy. CoNLL, 2020.

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A Rate–Distortion view of human pragmatic reasoning

Noga Zaslavsky, Jennifer Hu, Roger Levy. arXiv preprint, 2020.

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Toward human-like object naming in artificial neural systems

Tiwalayo Eisape, Roger Levy, Joshua Tenenbaum, Noga Zaslavsky. BAICS @ ICLR, 2020.

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Emergence of pragmatic reasoning from least-effort optimization

Noga Zaslavsky, Jennifer Hu, Roger Levy. EvoLang XIII, 2020.

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Information-Theoretic Principles in the Evolution of Semantic Systems

Noga Zaslavsky. PhD Thesis, The Hebrew University, 2020.

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Deterministic annealing and the evolution of Information Bottleneck representations

Noga Zaslavsky, Naftali Tishby. Technical report, 2019.

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Evolution and efficiency in color naming: The case of Nafaanra

Noga Zaslavsky*, Karee Garvin*, Charles Kemp, Naftali Tishby, Terry Regier. CogSci, 2019.

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Semantic categories of artifacts and animals reflect efficient coding

Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp. CogSci, 2019.

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Communicative need in color naming

Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier. CNP, 2019.

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Color naming reflects both perceptual structure and communicative need

Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier. topiCS, 2019.

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Efficient compression in color naming and its evolution

ELSC Prize for Outstanding Publication

Noga Zaslavsky, Charles Kemp, Terry Regier, Naftali Tishby. PNAS, 2018.

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Color naming reflects both perceptual structure and communicative need (earlier version)

Best paper award for computational modeling of language

Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier. CogSci, 2018.

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