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08/08/2023
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Synthetic image datasets offer unmatched advantages for designing and ev...
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07/24/2023
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?
For more than a decade, researchers have measured progress in object rec...
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06/01/2023
Birth of a Transformer: A Memory Viewpoint
Large language models based on transformers have achieved great empirica...
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04/11/2023
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies
Despite impressive advances in object-recognition, deep learning systems...
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11/03/2022
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
Deep learning vision systems are widely deployed across applications whe...
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10/24/2022
The Robustness Limits of SoTA Vision Models to Natural Variation
Recent state-of-the-art vision models introduced new architectures, lear...
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10/24/2022
Robust Self-Supervised Learning with Lie Groups
Deep learning has led to remarkable advances in computer vision. Even so...
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10/13/2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support
A grand goal in deep learning research is to learn representations capab...
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07/20/2022
Measuring and signing fairness as performance under multiple stakeholder distributions
As learning machines increase their influence on decisions concerning hu...
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06/09/2021
Grounding inductive biases in natural images:invariance stems from variations in data
To perform well on unseen and potentially out-of-distribution samples, i...
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02/10/2021
Addressing the Topological Defects of Disentanglement via Distributed Operators
A core challenge in Machine Learning is to learn to disentangle natural ...
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09/29/2020
Think before you act: A simple baseline for compositional generalization
Contrarily to humans who have the ability to recombine familiar expressi...
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04/20/2020
Compositionality and Generalization in Emergent Languages
Natural language allows us to refer to novel composite concepts by combi...
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03/11/2020
A Benchmark for Systematic Generalization in Grounded Language Understanding
Human language users easily interpret expressions that describe unfamili...
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11/05/2019
Focus on What's Informative and Ignore What's not: Communication Strategies in a Referential Game
Research in multi-agent cooperation has shown that artificial agents are...
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08/14/2019
Mastering emergent language: learning to guide in simulated navigation
To cooperate with humans effectively, virtual agents need to be able to ...
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07/01/2019
EGG: a toolkit for research on Emergence of lanGuage in Games
There is renewed interest in simulating language emergence among deep ne...
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05/31/2019
Information Minimization In Emergent Languages
There is a growing interest in studying the languages emerging when neur...
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05/28/2019
Miss Tools and Mr Fruit: Emergent communication in agents learning about object affordances
Recent research studies communication emergence in communities of deep n...
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05/28/2019
EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction
With the advent of deep neural networks, some research focuses towards u...
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08/31/2018
How agents see things: On visual representations in an emergent language game
There is growing interest in the language developed by agents interactin...
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05/24/2017
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations
We would like to learn a representation of the data which decomposes an ...
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06/08/2016
