565 citations · 2.5k across the 94 of their papers we have counts for
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On the Pitfalls of Analyzing Individual Neurons in Language Models
Omer Antverg, Yonatan Belinkov
While many studies have shown that linguistic information is encoded in hidden word representations, few have studied individual neurons, to show how and in which neurons it is enc…
Debiasing Methods in Natural Language Understanding Make Bias More Accessible
Michael Mendelson, Yonatan Belinkov
Model robustness to bias is often determined by the generalization on carefully designed out-of-distribution datasets. Recent debiasing methods in natural language understanding (N…
A Generative Approach for Mitigating Structural Biases in Natural Language Inference
Dimion Asael, Zachary Ziegler, Yonatan Belinkov
Many natural language inference (NLI) datasets contain biases that allow models to perform well by only using a biased subset of the input, without considering the remainder featur…
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann +3
Targeted syntactic evaluations have demonstrated the ability of language models to perform subject-verb agreement given difficult contexts. To elucidate the mechanisms by which the…
Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson
While large-scale pretrained language models have obtained impressive results when fine-tuned on a wide variety of tasks, they still often suffer from overfitting in low-resource s…
Supervising Model Attention with Human Explanations for Robust Natural Language Inference
Joe Stacey, Yonatan Belinkov, Marek Rei
Natural Language Inference (NLI) models are known to learn from biases and artefacts within their training data, impacting how well they generalise to other unseen datasets. Existi…
Probing Classifiers: Promises, Shortcomings, and Advances
Yonatan Belinkov
Probing classifiers have emerged as one of the prominent methodologies for interpreting and analyzing deep neural network models of natural language processing. The basic idea is s…