Kushal Tirumala
2022
Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks
Tristan Thrush
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Kushal Tirumala
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Anmol Gupta
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Max Bartolo
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Pedro Rodriguez
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Tariq Kane
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William Gaviria Rojas
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Peter Mattson
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Adina Williams
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Douwe Kiela
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
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-of-the-art NLP models, as well as for conducting model in the loop data collection with crowdworkers. Dynatask is integrated with Dynabench, a research platform for rethinking benchmarking in AI that facilitates human and model in the loop data collection and evaluation. To create a task, users only need to write a short task configuration file from which the relevant web interfaces and model hosting infrastructure are automatically generated. The system is available at https://dynabench.org/ and the full library can be found at https://github.com/facebookresearch/dynabench.
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Co-authors
- Tristan Thrush 1
- Anmol Gupta 1
- Max Bartolo 1
- Pedro Rodriguez 1
- Tariq Kane 1
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