Multimodality and Attention Increase Alignment in Natural Language Prediction Between Humans and Computational Models

no code implementations • 11 Aug 2023 • Viktor Kewenig, Andrew Lampinen, Samuel A. Nastase, Christopher Edwards, Quitterie Lacome DEstalenx, Akilles Rechardt, Jeremy I Skipper, Gabriella Vigliocco

Humans and computational models alike can leverage the predictive constraints of multimodal information by attending to relevant features in the input.

Does Conceptual Representation Require Embodiment? Insights From Large Language Models

no code implementations • 30 May 2023 • Qihui Xu, Yingying Peng, Samuel A. Nastase, Martin Chodorow, Minghua Wu, Ping Li

To what extent can language alone give rise to complex concepts, or is embodied experience essential?

A Data-Efficient Mutual Information Neural Estimator for Statistical Dependency Testing

no code implementations • 25 Sep 2019 • Xiao Lin, Indranil Sur, Samuel A. Nastase, Uri Hasson, Ajay Divakaran, Mohamed R. Amer

Measuring Mutual Information (MI) between high-dimensional, continuous, random variables from observed samples has wide theoretical and practical applications.

Meta-Learning

Data-Efficient Mutual Information Neural Estimator

no code implementations • 8 May 2019 • Xiao Lin, Indranil Sur, Samuel A. Nastase, Ajay Divakaran, Uri Hasson, Mohamed R. Amer

We demonstrate the effectiveness of our estimators on synthetic benchmarks and a real world fMRI data, with application of inter-subject correlation analysis.

Meta-Learning