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Oana Camburu

2 accepted papers

2022

Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations

ICML 2022spotlight

Models that generate extractive rationales (i.e., subsets of features) or natural language explanations (NLEs) for their predictions are important for explainable AI. While an extractive rationale provides a quick view of the features most responsible for a prediction, an NLE allows for a comprehens…

2016

Generation and Comprehension of Unambiguous Object Descriptions

CVPR 2016oral

We propose a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or interpret such an expression to infer which object is being described. We show that our method outperforms previous methods…

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