activity
20182021
collaborators

6 papers

cs.CL2021

Language Models Use Monotonicity to Assess NPI Licensing

Jaap Jumelet, Milica Denić, Jakub Szymanik +2

We investigate the semantic knowledge of language models (LMs), focusing on (1) whether these LMs create categories of linguistic environments based on their semantic monotonicity…

cs.CL2021

Attention vs non-attention for a Shapley-based explanation method

Tom Kersten, Hugh Mee Wong, Jaap Jumelet +1

The field of explainable AI has recently seen an explosion in the number of explanation methods for highly non-linear deep neural networks. The extent to which such methods -- that…

cs.CL2021

Language Modelling as a Multi-Task Problem

Lucas Weber, Jaap Jumelet, Elia Bruni +1

In this paper, we propose to study language modelling as a multi-task problem, bringing together three strands of research: multi-task learning, linguistics, and interpretability.…

cs.CL2020

diagNNose: A Library for Neural Activation Analysis

Jaap Jumelet

In this paper we introduce diagNNose, an open source library for analysing the activations of deep neural networks. diagNNose contains a wide array of interpretability techniques t…

cs.CL2019

Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment

Jaap Jumelet, Willem Zuidema, Dieuwke Hupkes

Extensive research has recently shown that recurrent neural language models are able to process a wide range of grammatical phenomena. How these models are able to perform these re…

cs.CL2018

Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items

Jaap Jumelet, Dieuwke Hupkes

In this paper, we attempt to link the inner workings of a neural language model to linguistic theory, focusing on a complex phenomenon well discussed in formal linguis- tics: (nega…