MilaNLP Lab

We are the Milan Natural Language Processing Group. We study, develop and deploy NLP algorithms to solve real-world problems.

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Meet the team!

Researchers

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Dirk Hovy

Full Professor

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Debora Nozza

Assistant Professor

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Arianna Muti

Postdoc

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Donya Rooein

Postdoc

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Elisa Bassignana

Visiting Postdoc

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Emanuele Moscato

Postdoc

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Flor Plaza

Postdoc

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Joachim Baumann

Visiting Researcher

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Paul Röttger

Postdoc

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Tanise Ceron

Postdoc

Alumni

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Amanda Cercas Curry

Researcher, CENTAI Institute

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Anne Lauscher

Associate Professor, University of Hamburg

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Federico Bianchi

Postdoc, Stanford University

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Tommaso Fornaciari

Direttore Tecnico Superiore della Polizia di Stato

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Giuseppe Attanasio

Postdoc

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Jan Globisz

Master’s student

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Kilian Theil

Researcher Associate, University of Mannheim

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Lorenzo Lupo

Postdoc

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Maria Nawrocka

Visiting PhD Student

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Matthias Orlikowski

PhD Student, Bielefeld University

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Nikita Soni

PhD Student, Stony Brook University

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Pieter Delobelle

PhD Student, KU Leuven

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Pietro Lesci

PhD student, Cambridge University

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Tiancheng Hu

Visiting PhD Student

Projects

INDOMITA

Innovative Demographically-aware Hate Speech Detection in Online Media in Italian

PERSONAE

Personalized and Subjective approaches to Natural Language Processing

MENTALISM

Measuring, Tracking, and Analyzing Inequality using Social Media

INTEGRATOR

Incorporating Demographic Factors into Natural Language Processing Models

Twitter Healthy Conversations

Devising Metrics for Assessing Echo Chambers, Incivility, and Intolerance on Twitter

Recent Twitter activity

Recent Publications

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The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

December, 2024
Human feedback is central to the alignment of Large Language Models (LLMs). However, open questions remain about methods (how), domains …
PDF Project

Language is Scary when Over-Analyzed: Unpacking Implied Misogynistic Reasoning with Argumentation Theory-Driven Prompts

November, 2024
We propose misogyny detection as an Argumentative Reasoning task and we investigate the capacity of large language models (LLMs) to …
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Countering Hateful and Offensive Speech Online - Open Challenges

September, 2024
In today’s digital age, hate speech and offensive speech online pose a significant challenge to maintaining respectful and inclusive …
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Divine LLaMAs: Bias, Stereotypes, Stigmatization, and Emotion Representation of Religion in Large Language Models

September, 2024
Emotions play important epistemological and cognitive roles in our lives, revealing our values and guiding our actions. Previous work …
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Compromesso! Italian Many-Shot Jailbreaks Undermine the Safety of Large Language Models

August, 2024
As diverse linguistic communities and users adopt large language models (LLMs), assessing their safety across languages becomes …
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