Papers by Giuseppe Sartori
ZeroNER: Fueling Zero-Shot Named Entity Recognition via Entity Type Descriptions (2025.findings-acl)
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Alessio Cocchieri, Marcos Martínez Galindo, Giacomo Frisoni, Gianluca Moro, Claudio Sartori, Giuseppe Tagliavini
| Challenge: | Existing zero-shot learning methods rely on entity type names for generalization . current solutions require large datasets and prioritize a handful of commonly occurring types . |
| Approach: | They propose a description-driven framework that enhances hard zero-shot NER in low-resource settings. |
| Outcome: | The proposed framework outperforms existing models by up to 16% in the F1 score . it also surpasses baseline models that use type names alone . |
DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text (2020.lrec-1)
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| Challenge: | Recent studies show that humans are ineffective in spotting deceit, with accuracy rates only slightly above the chance level. |
| Approach: | They propose a new language resource for automatic deception detection in cross-domain and cross-language scenarios. |
| Outcome: | The proposed language resource is composed of 5000 examples of truthful and deceitful first-person opinions across five different domains and two languages. |