Underreporting of errors in NLG output, and what to do about it
We observe a severe under-reporting of the different kinds of errors that Natural Language
Generation systems make. This is a problem, because mistakes are an important indicator of …
Generation systems make. This is a problem, because mistakes are an important indicator of …
ContextRef: Evaluating Referenceless Metrics For Image Description Generation
Referenceless metrics (eg, CLIPScore) use pretrained vision--language models to assess
image descriptions directly without costly ground-truth reference texts. Such methods can …
image descriptions directly without costly ground-truth reference texts. Such methods can …
NNEval: Neural network based evaluation metric for image captioning
N Sharif, L White, M Bennamoun… - Proceedings of the …, 2018 - openaccess.thecvf.com
The automatic evaluation of image descriptions is an intricate task, and it is highly important
in the development and fine-grained analysis of captioning systems. Existing metrics to …
in the development and fine-grained analysis of captioning systems. Existing metrics to …
Data curation for image captioning with text-to-image generative models
Recent advances in image captioning are driven by increasingly larger-scale vision--
language pretraining, relying on massive computational resources and increasingly large …
language pretraining, relying on massive computational resources and increasingly large …
Vision to language: Methods, metrics and datasets
Alan Turing's pioneering vision of machines in the 1950s, that are capable of thinking like
humans is still what Artificial Intelligence (AI) and Deep Learning research aspires to …
humans is still what Artificial Intelligence (AI) and Deep Learning research aspires to …
Gradations of error severity in automatic image descriptions
E Van Miltenburg, WT Lu, E Krahmer… - Proceedings of the …, 2020 - aclanthology.org
Earlier research has shown that evaluation metrics based on textual similarity (eg, BLEU,
CIDEr, Meteor) do not correlate well with human evaluation scores for automatically …
CIDEr, Meteor) do not correlate well with human evaluation scores for automatically …
Lceval: Learned composite metric for caption evaluation
Automatic evaluation metrics hold a fundamental importance in the development and fine-
grained analysis of captioning systems. While current evaluation metrics tend to achieve an …
grained analysis of captioning systems. While current evaluation metrics tend to achieve an …
The Role of Data Curation in Image Captioning
Image captioning models are typically trained by treating all samples equally, neglecting to
account for mismatched or otherwise difficult data points. In contrast, recent work has shown …
account for mismatched or otherwise difficult data points. In contrast, recent work has shown …
The role of image representations in vision to language tasks
Tasks that require modeling of both language and visual information, such as image
captioning, have become very popular in recent years. Most state-of-the-art approaches …
captioning, have become very popular in recent years. Most state-of-the-art approaches …
The Pragmatics of Image Description Generation
E Kreiss - 2023 - search.proquest.com
Finding true words that describe an image seems easy, but it is finding the right words for an
image that poses a communicative challenge. Describing an image to make it accessible for …
image that poses a communicative challenge. Describing an image to make it accessible for …