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ORCIDNoga Zaslavsky
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2020 – today
- 2023
[c16]Mora Maldonado, Noga Zaslavsky, Jennifer Culbertson:
Evidence for a language-independent conceptual representation of pronominal referents. CogSci 2023- [c15]Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie A. Shah:
Human-Guided Complexity-Controlled Abstractions. NeurIPS 2023 - [i9]Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie Shah:
Human-Guided Complexity-Controlled Abstractions. CoRR abs/2310.17550 (2023) - 2022
- [c14]Alicia M. Chen, Matthias Hofer, Moshe Poliak, Roger Levy, Noga Zaslavsky:
The emergence of discrete and systematic communication in a continuous signal-meaning space. CogSci 2022 - [c13]Irene Zhou, Jennifer Hu, Roger Levy, Noga Zaslavsky:
Teasing apart models of pragmatics using optimal reference game design. CogSci 2022 - [c12]Noga Zaslavsky:
The information geometry of pragmatic reasoning. ISAIM 2022 - [c11]Mycal Tucker, Roger Levy, Julie A. Shah, Noga Zaslavsky:
Trading off Utility, Informativeness, and Complexity in Emergent Communication. NeurIPS 2022 - [i8]Mycal Tucker, Julie Shah, Roger Levy, Noga Zaslavsky:
Towards Human-Agent Communication via the Information Bottleneck Principle. CoRR abs/2207.00088 (2022) - 2021
- [c10]Jennifer Hu, Noga Zaslavsky, Roger Levy:
Competition from novel features drives scalar inferences in reference games. CogSci 2021 - [c9]Noga Zaslavsky, Mora Maldonado, Jennifer Culbertson:
Let's talk (efficiently) about us: Person systems achieve near-optimal compression. CogSci 2021 - [c8]Irene Zhou, Jennifer Hu, Roger Levy, Noga Zaslavsky:
Empirical Support for a Rate-Distortion Account of Pragmatic Reasoning. CogSci 2021 - [i7]Anna A. Ivanova, John Hewitt, Noga Zaslavsky:
Probing artificial neural networks: insights from neuroscience. CoRR abs/2104.08197 (2021) - [i6]Jennifer Hu, Roger Levy, Noga Zaslavsky:
Scalable pragmatic communication via self-supervision. CoRR abs/2108.05799 (2021) - 2020
- [c7]Tiwalayo Eisape, Noga Zaslavsky
, Roger Levy:
Cloze Distillation: Improving Neural Language Models with Human Next-Word Prediction. CoNLL 2020: 609-619 - [i5]Noga Zaslavsky, Jennifer Hu, Roger P. Levy:
A Rate-Distortion view of human pragmatic reasoning. CoRR abs/2005.06641 (2020)
2010 – 2019
- 2019
- [j3]Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier:
Color Naming Reflects Both Perceptual Structure and Communicative Need. Top. Cogn. Sci. 11(1): 207-219 (2019) - [c6]Noga Zaslavsky, Karee Garvin, Charles Kemp, Naftali Tishby, Terry Regier:
Evolution and efficiency in color naming: The case of Nafaanra. CogSci 2019: 68 - [c5]Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp:
Semantic categories of artifacts and animals reflect efficient coding. CogSci 2019: 1254-1260 - [c4]Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier:
Communicative need and color naming. CogSci 2019: 3613 - [i4]Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp:
Semantic categories of artifacts and animals reflect efficient coding. CoRR abs/1905.04562 (2019) - 2018
- [j2]Noga Zaslavsky, Charles Kemp, Terry Regier, Naftali Tishby:
Efficient compression in color naming and its evolution. Proc. Natl. Acad. Sci. USA 115(31): 7937-7942 (2018) - [c3]Noga Zaslavsky, Charles Kemp, Terry Regier, Naftali Tishby:
Information-theoretic efficiency and semantic variation: The case of color naming. CogSci 2018 - [c2]Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier:
Color naming reflects both perceptual structure and communicative need. CogSci 2018 - [i3]Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier:
Color naming reflects both perceptual structure and communicative need. CoRR abs/1805.06165 (2018) - [i2]Noga Zaslavsky, Charles Kemp, Terry Regier, Naftali Tishby:
Efficient human-like semantic representations via the Information Bottleneck principle. CoRR abs/1808.03353 (2018) - 2017
- [j1]Siwei Wang, Alexander Borst, Noga Zaslavsky, Naftali Tishby, Idan Segev:
Efficient encoding of motion is mediated by gap junctions in the fly visual system. PLoS Comput. Biol. 13(12) (2017) - 2015
- [c1]Naftali Tishby, Noga Zaslavsky:
Deep learning and the information bottleneck principle. ITW 2015: 1-5 - [i1]Naftali Tishby, Noga Zaslavsky:
Deep Learning and the Information Bottleneck Principle. CoRR abs/1503.02406 (2015)
Coauthor Index
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