Papers by Oskar van der Wal

2 papers
Inseq: An Interpretability Toolkit for Sequence Generation Models (2023.acl-demo)

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Challenge: Recent studies focused on classification tasks while largely overlooking generation settings due to a lack of dedicated tools.
Approach: They propose to use Inseq to democratize access to interpretability analyses of sequence generation models by enabling intuitive extraction of models’ internal information and feature importance scores for popular decoder-only and encoder-decoder Transformers architectures.
Outcome: The proposed library can extract models’ internal information and feature importance scores for popular decoder-only and encoder-decoder Transformers architectures.
The Grammar of Emergent Languages (2020.emnlp-main)

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Challenge: Existing studies on emergent languages focus on semantics, but lack tools to analyse their properties.
Approach: They propose to use unsupervised grammar induction techniques to analyse emergent languages and to examine their syntactic properties.
Outcome: The proposed techniques are appropriate to analyse emergent languages and show that they exhibit syntactic properties similar to those observed in human language.

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