430 citations · 1.5k across the 43 of their papers we have counts for
7 papers · 1 filter
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
Amir Feder, Katherine A. Keith, Emaad Manzoor +10
A fundamental goal of scientific research is to learn about causal relationships. However, despite its critical role in the life and social sciences, causality has not had the same…
Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information
Yuval Pinter, Amanda Stent, Mark Dredze +1
Commonly-used transformer language models depend on a tokenization schema which sets an unchangeable subword vocabulary prior to pre-training, destined to be applied to all downstr…
Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer
Iulia Turc, Kenton Lee, Jacob Eisenstein +2
Despite their success, large pre-trained multilingual models have not completely alleviated the need for labeled data, which is cumbersome to collect for all target languages. Zero…
The MultiBERTs: BERT Reproductions for Robustness Analysis
Thibault Sellam, Steve Yadlowsky, Jason Wei +9
Experiments with pre-trained models such as BERT are often based on a single checkpoint. While the conclusions drawn apply to the artifact tested in the experiment (i.e., the parti…
Time-Aware Language Models as Temporal Knowledge Bases
Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos +3
Many facts come with an expiration date, from the name of the President to the basketball team Lebron James plays for. But language models (LMs) are trained on snapshots of data co…
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
Victor Veitch, Alexander D'Amour, Steve Yadlowsky +1
Informally, a 'spurious correlation' is the dependence of a model on some aspect of the input data that an analyst thinks shouldn't matter. In machine learning, these have a know-i…