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Alissa Ostapenko

2 accepted papers

2023

GlobalBench: A Benchmark for Global Progress in Natural Language Processing

EMNLP 2023long main

Despite the major advances in NLP, significant disparities in NLP system performance across languages still exist. Arguably, these are due to uneven resource allocation and sub-optimal incentives to work on less resourced languages. To track and further incentivize the global development of equitabl…

Cited by 0SourceScholar
2022

Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching

ACL 2022long

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 relevant to the task. We hypothesize that enriching models with speaker information in a controlled, educated way can g…