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    • Advancing soil texture and organic carbon spatial variability assessment: Integrating proximal γ-ray spectroscopy and electromagnetic induction via data fusion for site-independent analysis
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    • AI for the Restoration of Ancient Inscriptions: A Computational Linguistics Perspective
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    • Improving Multi-lingual Medical Term Normalization to Address the Long-Tail Problem
    • Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Contexts
    • Extensive evaluation of transformer-based architectures for adverse drug events extraction
    • A Comparison of Mutual Information, Linear Models and Deep Learning Networks for Protein Secondary Structure Prediction
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    • Filling the Lacunae in ancient Latin inscriptions
    • Can the crowd judge truthfulness? A longitudinal study on recent misinformation about COVID-19
    • Detection of Adverse Drug Events from Social Media Texts-Research Project Overview
    • Generalizing over Long Tail Concepts for Medical Term Normalization
    • Increasing adverse drug events extraction robustness on social media: Case study on negation and speculation
    • AILAB-Udine@SMM4H 22: Limits of Transformers and BERT Ensembles
    • Negation detection for robust Adverse Drug Event extraction from social media texts
    • Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets
    • Improving adverse drug event extraction with SpanBERT on different text typologies
    • DiLBERT: Cheap Embeddings for Disease Related Medical NLP
    • NADE: A Benchmark for Robust Adverse Drug Events Extraction in Face of Negations
    • BERT Prescriptions to Avoid Unwanted Headaches: A Comparison of Transformer Architectures for Adverse Drug Event Detection
    • Efficient keyphrase generation with gans
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    • The covid-19 infodemic: Can the crowd judge recent misinformation objectively?
    • Distilling the evidence to augment fact verification models
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Beatrice Portelli
Authors
Beatrice Portelli
Post-doc Research Fellow
01 Jan 0001 →

© 2026 Beatrice Portelli. This work is licensed under CC BY NC ND 4.0

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