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PDF) The paradox of the compositionality of natural language: a neural  machine translation case study
PDF) The paradox of the compositionality of natural language: a neural machine translation case study

Snowmass2021 - Letter of Interest Cosmology Intertwined IV: The Age of the  Universe and its Curvature
Snowmass2021 - Letter of Interest Cosmology Intertwined IV: The Age of the Universe and its Curvature

A Minimal Model for Compositional Generalization on gSCAN
A Minimal Model for Compositional Generalization on gSCAN

PDF) Gaussian Visual-Linguistic Embedding for Zero-Shot Recognition
PDF) Gaussian Visual-Linguistic Embedding for Zero-Shot Recognition

The Emergence of the Shape Bias Results from Communicative Efficiency
The Emergence of the Shape Bias Results from Communicative Efficiency

Combinations of scales used for analysis. Terms) in each cell indicate... |  Download Table
Combinations of scales used for analysis. Terms) in each cell indicate... | Download Table

Dialogue Modelling Group
Dialogue Modelling Group

FIGURE1. The iterative system development process for COTS and... |  Download Scientific Diagram
FIGURE1. The iterative system development process for COTS and... | Download Scientific Diagram

A Minimal Model for Compositional Generalization on gSCAN
A Minimal Model for Compositional Generalization on gSCAN

Cooking Under Pressure, That's Reality - The New York Times
Cooking Under Pressure, That's Reality - The New York Times

PDF) Exploiting Language Instructions for Interpretable and Compositional  Reinforcement Learning
PDF) Exploiting Language Instructions for Interpretable and Compositional Reinforcement Learning

Combinations of scales used for analysis. Terms) in each cell indicate... |  Download Table
Combinations of scales used for analysis. Terms) in each cell indicate... | Download Table

Bottines ELIA BRUNI Femme | Achetez en ligne sur Micolet.fr
Bottines ELIA BRUNI Femme | Achetez en ligne sur Micolet.fr

PDF) Compositionality Decomposed: How do Neural Networks Generalise?
PDF) Compositionality Decomposed: How do Neural Networks Generalise?

arXiv:1809.06194v2 [cs.CL] 2 Apr 2019
arXiv:1809.06194v2 [cs.CL] 2 Apr 2019

Augmenting Classic Algorithms with Neural Components for Strong  Generalisation on Ambiguous and High-Dimensional Data
Augmenting Classic Algorithms with Neural Components for Strong Generalisation on Ambiguous and High-Dimensional Data

PDF) The Grammar of Emergent Languages
PDF) The Grammar of Emergent Languages

The EOS Decision and Length Extrapolation
The EOS Decision and Length Extrapolation

PDF) Multimodal Distributional Semantics
PDF) Multimodal Distributional Semantics

Capacity, Bandwidth, and Compositionality in Emergent Language Learning
Capacity, Bandwidth, and Compositionality in Emergent Language Learning

Sensorimotor distance: A grounded measure of semantic similarity for 800  million concept pairs | SpringerLink
Sensorimotor distance: A grounded measure of semantic similarity for 800 million concept pairs | SpringerLink

Reading visually embodied meaning from the brain: Visually grounded  computational models decode visual-object mental imagery induced by written  text - ScienceDirect
Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text - ScienceDirect