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1
Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality ...
Abstract: We present a novel task and dataset for evaluating the ability of vision and language models to conduct visio-linguistic compositional reasoning, which we call Winoground. Given two images and two captions, the goal is to match them correctly - but crucially, both captions contain a completely identical set of words, only in a different order. The dataset was carefully hand-curated by expert annotators and is labeled with a rich set of fine-grained tags to assist in analyzing model performance. We probe a diverse range of state-of-the-art vision and language models and find that, surprisingly, none of them do much better than chance. Evidently, these models are not as skilled at visio-linguistic compositional reasoning as we might have hoped. We perform an extensive analysis to obtain insights into how future work might try to mitigate these models' shortcomings. We aim for Winoground to serve as a useful evaluation set for advancing the state of the art and driving further progress in the field. The dataset ... : CVPR 2022 ...
Keyword: Computation and Language cs.CL; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2204.03162
https://arxiv.org/abs/2204.03162
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2
ANLIzing the Adversarial Natural Language Inference Dataset
In: Proceedings of the Society for Computation in Linguistics (2022)
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3
Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization
In: Association for Computational Linguistics (2021)
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4
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ...
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5
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation ...
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6
Compositional Neural Machine Translation by Removing the Lexicon from Syntax ...
Thrush, Tristan. - : arXiv, 2020
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7
SAL : a Self-Aware Learning system ; Self-Aware Learning system
Thrush, Tristan Andrew Fraser.. - : Massachusetts Institute of Technology, 2019
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