25 citations · 106 across the 16 of their papers we have counts for
16 papers
MSTS: A Multimodal Safety Test Suite for Vision-Language Models
Paul Röttger, Giuseppe Attanasio, Felix Friedrich +19
Vision-language models (VLMs), which process image and text inputs, are increasingly integrated into chat assistants and other consumer AI applications. Without proper safeguards,…
Classist Tools: Social Class Correlates with Performance in NLP
Amanda Cercas Curry, Giuseppe Attanasio, Zeerak Talat +1
Since the foundational work of William Labov on the social stratification of language (Labov, 1964), linguistics has made concentrated efforts to explore the links between sociodem…
Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps
Giuseppe Attanasio, Beatrice Savoldi, Dennis Fucci +1
Current automatic speech recognition (ASR) models are designed to be used across many languages and tasks without substantial changes. However, this broad language coverage hides p…
A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation
Giuseppe Attanasio, Flor Miriam Plaza-del-Arco, Debora Nozza +1
Recent instruction fine-tuned models can solve multiple NLP tasks when prompted to do so, with machine translation (MT) being a prominent use case. However, current research often…
Explaining Speech Classification Models via Word-Level Audio Segments and Paralinguistic Features
Eliana Pastor, Alkis Koudounas, Giuseppe Attanasio +2
Recent advances in eXplainable AI (XAI) have provided new insights into how models for vision, language, and tabular data operate. However, few approaches exist for understanding s…
Weigh Your Own Words: Improving Hate Speech Counter Narrative Generation via Attention Regularization
Helena Bonaldi, Giuseppe Attanasio, Debora Nozza +1
Recent computational approaches for combating online hate speech involve the automatic generation of counter narratives by adapting Pretrained Transformer-based Language Models (PL…
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio +4
Training large language models to follow instructions makes them perform better on a wide range of tasks and generally become more helpful. However, a perfectly helpful model will…
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
Paul Röttger, Hannah Rose Kirk, Bertie Vidgen +3
Without proper safeguards, large language models will readily follow malicious instructions and generate toxic content. This risk motivates safety efforts such as red-teaming and l…
ITALIC: An Italian Intent Classification Dataset
Alkis Koudounas, Moreno La Quatra, Lorenzo Vaiani +5
Recent large-scale Spoken Language Understanding datasets focus predominantly on English and do not account for language-specific phenomena such as particular phonemes or words in…
E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender Systems
Patrick John Chia, Giuseppe Attanasio, Jacopo Tagliabue +5
Recommender Systems today are still mostly evaluated in terms of accuracy, with other aspects beyond the immediate relevance of recommendations, such as diversity, long-term user r…
Is It Worth the (Environmental) Cost? Limited Evidence for Temporal Adaptation via Continuous Training
Giuseppe Attanasio, Debora Nozza, Federico Bianchi +1
Language is constantly changing and evolving, leaving language models to become quickly outdated. Consequently, we should continuously update our models with new data to expose the…
EvalRS: a Rounded Evaluation of Recommender Systems
Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel +4
Much of the complexity of Recommender Systems (RSs) comes from the fact that they are used as part of more complex applications and affect user experience through a varied range of…
ferret: a Framework for Benchmarking Explainers on Transformers
Giuseppe Attanasio, Eliana Pastor, Chiara Di Bonaventura +1
As Transformers are increasingly relied upon to solve complex NLP problems, there is an increased need for their decisions to be humanly interpretable. While several explainable AI…
Contrastive language and vision learning of general fashion concepts
Patrick John Chia, Giuseppe Attanasio, Federico Bianchi +5
The steady rise of online shopping goes hand in hand with the development of increasingly complex ML and NLP models. While most use cases are cast as specialized supervised learnin…
Entropy-based Attention Regularization Frees Unintended Bias Mitigation from Lists
Giuseppe Attanasio, Debora Nozza, Dirk Hovy +1
Natural Language Processing (NLP) models risk overfitting to specific terms in the training data, thereby reducing their performance, fairness, and generalizability. E.g., neural h…
Contrastive Language-Image Pre-training for the Italian Language
Federico Bianchi, Giuseppe Attanasio, Raphael Pisoni +3
CLIP (Contrastive Language-Image Pre-training) is a very recent multi-modal model that jointly learns representations of images and texts. The model is trained on a massive amount…