430 citations · 1.5k across the 43 of their papers we have counts for
5 papers · 1 filter
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan +37
ML models often exhibit unexpectedly poor behavior when they are deployed in real-world domains. We identify underspecification as a key reason for these failures. An ML pipeline i…
Learning to Recognize Dialect Features
Dorottya Demszky, Devyani Sharma, Jonathan H. Clark +2
Building NLP systems that serve everyone requires accounting for dialect differences. But dialects are not monolithic entities: rather, distinctions between and within dialects are…
Will it Unblend?
Yuval Pinter, Cassandra L. Jacobs, Jacob Eisenstein
Natural language processing systems often struggle with out-of-vocabulary (OOV) terms, which do not appear in training data. Blends, such as "innoventor", are one particularly chal…
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation
Yong Cheng, Lu Jiang, Wolfgang Macherey +1
In this paper, we propose a new adversarial augmentation method for Neural Machine Translation (NMT). The main idea is to minimize the vicinal risk over virtual sentences sampled f…
Sparse, Dense, and Attentional Representations for Text Retrieval
Yi Luan, Jacob Eisenstein, Kristina Toutanova +1
Dual encoders perform retrieval by encoding documents and queries into dense lowdimensional vectors, scoring each document by its inner product with the query. We investigate the c…