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05/23/2023
Weakly-Supervised Learning of Visual Relations in Multimodal Pretraining
Recent work in vision-and-language pretraining has investigated supervis...
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05/12/2023
Measuring Progress in Fine-grained Vision-and-Language Understanding
While pretraining on large-scale image-text data from the Web has facili...
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03/13/2023
Evaluating Visual Number Discrimination in Deep Neural Networks
The ability to discriminate between large and small quantities is a core...
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11/15/2022
Pragmatics in Grounded Language Learning: Phenomena, Tasks, and Modeling Approaches
People rely heavily on context to enrich meaning beyond what is literall...
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10/13/2022
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Large pre-trained models have proved to be remarkable zero- and (prompt-...
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05/24/2022
Rethinking Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization
Vision-and-language (V L) models pretrained on large-scale multimodal ...
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04/29/2022
Flamingo: a Visual Language Model for Few-Shot Learning
Building models that can be rapidly adapted to numerous tasks using only...
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10/31/2021
A Systematic Investigation of Commonsense Understanding in Large Language Models
Large language models have shown impressive performance on many natural ...
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06/16/2021
Probing Image-Language Transformers for Verb Understanding
Multimodal image-language transformers have achieved impressive results ...
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01/31/2021
Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers
Recently multimodal transformer models have gained popularity because th...
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12/06/2020
Competition in Cross-situational Word Learning: A Computational Study
Children learn word meanings by tapping into the commonalities across di...
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05/07/2020
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narra...
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03/11/2020
Visual Grounding in Video for Unsupervised Word Translation
There are thousands of actively spoken languages on Earth, but a single ...
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08/28/2018
Evaluating Theory of Mind in Question Answering
We propose a new dataset for evaluating question answering models with r...
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05/19/2018
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels
Modern convolutional neural networks (CNNs) are able to achieve human-le...
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11/29/2017
Predicting and Explaining Human Semantic Search in a Cognitive Model
Recent work has attempted to characterize the structure of semantic memo...
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02/22/2017
Calculating Probabilities Simplifies Word Learning
Children can use the statistical regularities of their environment to le...
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02/18/2016
The Interaction of Memory and Attention in Novel Word Generalization: A Computational Investigation
People exhibit a tendency to generalize a novel noun to the basic-level ...
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02/10/2016