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Who are you referring to? Weakly supervised coreference resolution with multimodal grounding

2022-11-26 13:33:42
Arushi Goel, Basura Fernando, Frank Keller, Hakan Bilen
arXiv_CV
         
Abstract

Coreference resolution aims at identifying words and phrases which refer to same entity in a text, a core tool in natural language processing. In this paper, we propose a novel task, resolving coreferences in multimodal data, long-form textual descriptions of visual scenes. Most existing image-text datasets only contain short sentences without coreferent expressions, or coreferences are not annotated. To this end, we first introduce a new dataset, Flickr30k-Coref in which coreference chains and bounding box localization of these chains are annotated. We propose a new technique that learns to identify coreference chains through weakly supervised grounding from image-text pairs and a regularization using prior linguistic knowledge. Our model yields large performance gains over prior work in coreference resolution and weakly supervised grounding of long-form text descriptions.

Abstract (translated)

URL

https://arxiv.org/abs/2211.14563

PDF

https://arxiv.org/pdf/2211.14563.pdf

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