19 citations · 77 across the 17 of their papers we have counts for
43 papers
Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching
Alissa Ostapenko, Shuly Wintner, Melinda Fricke +1
Natural language processing (NLP) models trained on people-generated data can be unreliable because, without any constraints, they can learn from spurious correlations that are not…
Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs
Monisha Jegadeesan, Sachin Kumar, John Wieting +1
We present a novel technique for zero-shot paraphrase generation. The key contribution is an end-to-end multilingual paraphrasing model that is trained using translated parallel co…
Detecting Community Sensitive Norm Violations in Online Conversations
Chan Young Park, Julia Mendelsohn, Karthik Radhakrishnan +4
Online platforms and communities establish their own norms that govern what behavior is acceptable within the community. Substantial effort in NLP has focused on identifying unacce…
Efficient Test Time Adapter Ensembling for Low-resource Language Varieties
Xinyi Wang, Yulia Tsvetkov, Sebastian Ruder +1
Adapters are light-weight modules that allow parameter-efficient fine-tuning of pretrained models. Specialized language and task adapters have recently been proposed to facilitate…
A Survey of Race, Racism, and Anti-Racism in NLP
Anjalie Field, Su Lin Blodgett, Zeerak Waseem +1
Despite inextricable ties between race and language, little work has considered race in NLP research and development. In this work, we survey 79 papers from the ACL anthology that…
Machine Translation into Low-resource Language Varieties
Sachin Kumar, Antonios Anastasopoulos, Shuly Wintner +1
State-of-the-art machine translation (MT) systems are typically trained to generate the "standard" target language; however, many languages have multiple varieties (regional variet…