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 .
