2.7k citations · 2.8k across the 16 of their papers we have counts for
7 papers · 1 filter
A Word on Machine Ethics: A Response to Jiang et al. (2021)
Zeerak Talat, Hagen Blix, Josef Valvoda +3
Ethics is one of the longest standing intellectual endeavors of humanity. In recent years, the fields of AI and NLP have attempted to wrangle with how learning systems that interac…
Analyzing Dynamic Adversarial Training Data in the Limit
Eric Wallace, Adina Williams, Robin Jia +1
To create models that are robust across a wide range of test inputs, training datasets should include diverse examples that span numerous phenomena. Dynamic adversarial data collec…
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking
Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush +6
We introduce Dynaboard, an evaluation-as-a-service framework for hosting benchmarks and conducting holistic model comparison, integrated with the Dynabench platform. Our platform e…
Investigating Failures of Automatic Translation in the Case of Unambiguous Gender
Adithya Renduchintala, Adina Williams
Transformer based models are the modern work horses for neural machine translation (NMT), reaching state of the art across several benchmarks. Despite their impressive accuracy, we…
Sometimes We Want Translationese
Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau +1
Rapid progress in Neural Machine Translation (NMT) systems over the last few years has been driven primarily towards improving translation quality, and as a secondary focus, improv…
Dynabench: Rethinking Benchmarking in NLP
Douwe Kiela, Max Bartolo, Yixin Nie +16
We introduce Dynabench, an open-source platform for dynamic dataset creation and model benchmarking. Dynabench runs in a web browser and supports human-and-model-in-the-loop datase…
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little
Koustuv Sinha, Robin Jia, Dieuwke Hupkes +3
A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent i…