Inseq: An Interpretability Toolkit for Sequence Generation Models | Gabriele Sarti
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Inseq: An Interpretability Toolkit for Sequence Generation Models
Gabriele Sarti
Natural Language Processing
,
Academic
Code
Project
Slides
Date
Apr 6, 2023
Event
SapienzaNLP Invited Talk
Location
Sapienza University of Rome
Natural Language Processing
Interpretability
Sequence-to-sequence
Language Modeling
Feature Attribution
Related
Advanced XAI Techniques and Inseq: An Interpretability Toolkit for Sequence Generation Models
Explaining Language Models with Inseq
Introducing Inseq: An Interpretability Toolkit for Sequence Generation Models
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
Towards User-centric Interpretability of Machine Translation Models
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