mlsanityData to 14 Oct 2026

Who are you referring to? Coreference resolution in image narrations

arXiv 2211.14563 ↗First posted 26 Nov 2022cs.CV cs.CLcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 41 of its 71 references that are in the map. First posted on arXiv 26 Nov 2022.

Builds on

41 of 71 references.

References · 41

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29 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.