Post-hoc Interpretability for NLG & Inseq: an Interpretability Toolkit for Sequence Generation Models | Gabriele Sarti
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Post-hoc Interpretability for NLG & Inseq: an Interpretability Toolkit for Sequence Generation Models
Gabriele Sarti
Natural Language Processing
,
Academic
Code
Project
Slides
Date
Jul 2, 2023
Event
Tutorial at REST-CL, Universitat Pompeu Fabra
Location
L’Arboç, Tarragona, Spain
Natural Language Processing
Interpretability
Sequence-to-sequence
Language Modeling
Feature Attribution
Related
Explaining Neural Language Models from Internal Representations to Model Predictions
Post-hoc Interpretability for Neural Language Models
Post-hoc Interpretability for Neural Language Models
Advanced XAI Techniques and Inseq: An Interpretability Toolkit for Sequence Generation Models
Explaining Language Models with Inseq
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