Search Results for author: Raja Marjieh

Found 14 papers, 3 papers with code

A Rational Analysis of the Speech-to-Song Illusion

no code implementations10 Feb 2024 Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Thomas L. Griffiths, Nori Jacoby

Here we provide a formal account of this phenomenon, by recasting it as a statistical inference whereby a rational agent attempts to decide whether a sequence of utterances is more likely to have been produced in a song or speech.


Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction

no code implementations6 Feb 2024 Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden Lake, Thomas L. Griffiths

To investigate the effect language on the formation of abstractions, we implement a novel multimodal serial reproduction framework by asking people who receive a visual stimulus to reproduce it in a linguistic format, and vice versa.

The Universal Law of Generalization Holds for Naturalistic Stimuli

no code implementations14 Jun 2023 Raja Marjieh, Nori Jacoby, Joshua C. Peterson, Thomas L. Griffiths

Shepard's universal law of generalization is a remarkable hypothesis about how intelligent organisms should perceive similarity.

Around the world in 60 words: A generative vocabulary test for online research

no code implementations3 Feb 2023 Pol van Rijn, Yue Sun, Harin Lee, Raja Marjieh, Ilia Sucholutsky, Francesca Lanzarini, Elisabeth André, Nori Jacoby

Six behavioral experiments (N=236) in six countries and eight languages show that (a) our test can distinguish between native speakers of closely related languages, (b) the test is reliable ($r=0. 82$), and (c) performance strongly correlates with existing tests (LexTale) and self-reports.

Cultural Vocal Bursts Intensity Prediction

Large language models predict human sensory judgments across six modalities

no code implementations2 Feb 2023 Raja Marjieh, Ilia Sucholutsky, Pol van Rijn, Nori Jacoby, Thomas L. Griffiths

Determining the extent to which the perceptual world can be recovered from language is a longstanding problem in philosophy and cognitive science.


Analyzing Diffusion as Serial Reproduction

no code implementations29 Sep 2022 Raja Marjieh, Ilia Sucholutsky, Thomas A. Langlois, Nori Jacoby, Thomas L. Griffiths

Diffusion models are a class of generative models that learn to synthesize samples by inverting a diffusion process that gradually maps data into noise.


Words are all you need? Language as an approximation for human similarity judgments

no code implementations8 Jun 2022 Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Theodore R. Sumers, Harin Lee, Thomas L. Griffiths, Nori Jacoby

Based on the results of this comprehensive study, we provide a concise guide for researchers interested in collecting or approximating human similarity data.

Contrastive Learning Information Retrieval +2

Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines

1 code implementation23 May 2022 Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Nathaniel D. Daw, Jonathan D. Cohen, Karthik Narasimhan, Thomas L. Griffiths

Co-training on these representations result in more human-like behavior in downstream meta-reinforcement learning agents than less abstract controls (synthetic language descriptions, program induction without learned primitives), suggesting that the abstraction supported by these representations is key.

Meta-Learning Meta Reinforcement Learning +2

Predicting Human Similarity Judgments Using Large Language Models

no code implementations9 Feb 2022 Raja Marjieh, Ilia Sucholutsky, Theodore R. Sumers, Nori Jacoby, Thomas L. Griffiths

Similarity judgments provide a well-established method for accessing mental representations, with applications in psychology, neuroscience and machine learning.

Gibbs Sampling with People

no code implementations NeurIPS 2020 Peter M. C. Harrison, Raja Marjieh, Federico Adolfi, Pol van Rijn, Manuel Anglada-Tort, Ofer Tchernichovski, Pauline Larrouy-Maestri, Nori Jacoby

We formulate both methods from a utility-theory perspective, and show that the new method can be interpreted as 'Gibbs Sampling with People' (GSP).

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