Pau Rodríguez

Beyond Trivial Counterfactual Generations with Diverse Valuable Explanations

2021

Explainability of machine learning models has gained considerable attention within our research community given the importance of deploying more reliable machine-learning systems. Explanability can also be helpful for model debugging. In computer vision applications, most …

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models

2022 · arXiv (Cornell University)

Data augmentation is a widely employed technique to alleviate the problem of data scarcity. In this work, we propose a prompting-based approach to generate labelled training data for intent classification with off-the-shelf language models (LMs) …