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Alberto Purpura

3 accepted papers

2025

GRAID: Synthetic Data Generation with Geometric Constraints and Multi-Agentic Reflection for Harmful Content Detection

EMNLP 2025

We address the problem of data scarcity in harmful text classification for guardrailing applications and introduce GRAID (Geometric and Reflective AI-Driven Data Augmentation), a novel pipeline that leverages Large Language Models (LLMs) for dataset augmentation. GRAID consists of two stages: (i) ge

Cited by 0SourcePDFScholar
2024

Description Boosting for Zero-Shot Entity and Relation Classification

ACL 2024findings

Zero-shot entity and relation classification models leverage available external information of unseen classes – e.g., textual descriptions – to annotate input text data. Thanks to the minimum data requirement, Zero-Shot Learning (ZSL) methods have high value in practice, especially in applications w…

2022

Accelerating the Discovery of Semantic Associations from Medical Literature: Mining Relations Between Diseases and Symptoms

EMNLP 2022industry

Medical literature is a vast and constantly expanding source of information about diseases, their diagnoses and treatments. One of the ways to extract insights from this type of data is through mining association rules between such entities. However, existing solutions do not take into account the s…

Cited by 2SourcePDFScholar