arXivDaily arXiv每日学术速递 周一至周五更新
​通知:联邦节假日调休:哥伦布日 / 原住民日(Columbus Day / Indigenous Peoples' Day),今日(13日)无更新。
arXiv 2211.14563cs.CVcs.CL

Who are you referring to? Coreference resolution in image narrations

School of Informatics, University of Edinburgh(爱丁堡大学信息学院);CFAR, IHPC, A*STAR(新加坡科技研究局高性能计算研究所认知智能研究中心)

Arushi Goel, Basura Fernando, Frank Keller, Hakan Bilen

英文摘要:

Coreference resolution aims to identify words and phrases which refer to same entity in a text, a core task in natural language processing. In this paper, we extend this task to resolving coreferences in long-form narrations of visual scenes. First we introduce a new dataset with annotated coreference chains and their bounding boxes, as most existing image-text datasets only contain short sentences without coreferring expressions or labeled chains. We propose a new technique that learns to identify coreference chains using weak supervision, only from image-text pairs and a regularization using prior linguistic knowledge. Our model yields large performance gains over several strong baselines in resolving coreferences. We also show that coreference resolution helps improving grounding narratives in images.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑