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The intersection of Interpretability and Fairness

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If you have a question about this talk, please contact Richard Diehl Martinez.

A survey of methods of interpretability of neural networks: from gender bias mitigation to interpreting BERT embeddings in a psycholinguistic manner.

Bio:

Giuseppe Attanasio is a postdoctoral researcher affiliated with the Milan Natural Language Processing (MilaNLP) Lab at Bocconi University. His research primarily focuses on large-scale neural architectures for Natural Language Processing.

Attanasio has contributed to various research projects and publications in the field of NLP . Notably, he has worked on topics such as automatic misogyny identification, benchmarking post-hoc interpretability approaches for transformer-based models, and entropy-based attention regularization for bias mitigation. His work often involves the development and deployment of NLP algorithms to address real-world problems .

This talk is part of the NLIP Seminar Series series.

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