29 citations · 55 across the 27 of their papers we have counts for
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cs.CL2023
InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations
Nils Feldhus, Qianli Wang, Tatiana Anikina +3
While recently developed NLP explainability methods let us open the black box in various ways (Madsen et al., 2022), a missing ingredient in this endeavor is an interactive tool of…
cs.CL2023★ 29 cited
Inseq: An Interpretability Toolkit for Sequence Generation Models
Gabriele Sarti, Nils Feldhus, Ludwig Sickert +3
Past work in natural language processing interpretability focused mainly on popular classification tasks while largely overlooking generation settings, partly due to a lack of dedi…