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Andrea Bartezzaghi

3 accepted papers

2024

Probabilistic Feature Matching for Fast Scalable Visual Prompting

IJCAI 2024poster

In this work, we propose a novel framework for image segmentation guided by visual prompting which leverages the power of vision foundation models. Inspired by recent advancements in computer vision, our approach integrates multiple large-scale pretrained models to address the challenges of segment…

Cited by 1SourcePDFScholar
2024

Prompting-based Synthetic Data Generation for Few-Shot Question Answering

COLING 2024main

Although language models (LMs) have boosted the performance of Question Answering, they still need plenty of data. Data annotation, in contrast, is a time-consuming process. This especially applies to Question Answering, where possibly large documents have to be parsed and annotated with questions a…