most citedDynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking

16 citations · 49 across the 6 of their papers we have counts for

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cs.CL20222 cited

Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks

Tristan Thrush, Kushal Tirumala, Anmol Gupta +7

We introduce Dynatask: an open source system for setting up custom NLP tasks that aims to greatly lower the technical knowledge and effort required for hosting and evaluating state…

cs.CL20211 cited

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…

cs.CL202116 cited

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…

cs.CL202112 cited

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…

cs.CL20214 cited

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…

cs.CL2021

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…