natural-language-processing-4
Grounded Open Vocabulary Acquisition
3260 papers • 126 benchmarks • 313 datasets
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Most implemented papers
World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models
J. Chai, Ziqiao Ma, Jiayi Pan•Tue Jun 13 2023
This work proposes World-to-Words (W2W), a novel visually-grounded language model by pre-training on image-text pairs highlighting grounding as an objective, and demonstrates that W2W is a more coherent and fast grounded word learner, and that the grounding ability acquired during pre- training helps the model to learn unseen words more rapidly and robustly.
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