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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Amanda Cercas Curry

Postdoc

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Donya Rooein

Postdoc

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Flor Plaza

Postdoc

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Giuseppe Attanasio

Postdoc

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Lorenzo Lupo

Postdoc

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Paul Röttger

Postdoc

Alumni

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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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Jan Globisz

Master’s student

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Kilian Theil

Researcher Associate, University of Mannheim

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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

Projects

INDOMITA

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

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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DADIT: A Dataset for Demographic Classification of Italian Twitter Users and a Comparison of Prediction Methods

May, 2024
Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the …
PDF Project

Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution

March, 2024
Large language models (LLMs) reflect societal norms and biases, especially about gender. While societal biases and stereotypes have …
PDF Project

Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions

March, 2024
Emotions are a central aspect of communication. Consequently, emotion analysis (EA) is a rapidly growing field in natural language …
PDF Project

The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising 'Alignment' in Large Language Models

November, 2023
In this paper, we address the concept of ‘alignment’ in large language models (LLMs) through the lens of post-structuralist …
PDF Project Project

SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models

November, 2023
The past year has seen rapid acceleration in the development of large language models (LLMs). For many tasks, there is now a wide range …
PDF Project Project
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