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Crowdsourced dialogue corpora are usually limited in scale and topic coverage due to the expensive cost of data curation.
Measuring nominal scale agreement among many raters
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Fightin’words: Lexical feature selection and evaluation for identifying the content of political conflict
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A diversity-promoting objective function for neural conversation models
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How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
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Personalizing dialogue agents: I have a dog, do you have pets too?
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The curious case of neural text degeneration
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Language models are unsupervised multitask learners
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Towards empathetic open-domain conversation models: A new benchmark and dataset
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The risk of racial bias in hate speech detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A Smith. 2019 · 2019
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Language models are few-shot learners
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Toxicity detection: Does context really matter?
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Comae: A multi-factor hierarchical framework for empathetic response generation
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Eva: An open-domain chinese dialogue system with large-scale generative pre-training
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Is gpt-3 text indistinguishable from human text? scarecrow: A framework for scrutinizing machine text
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Transformers: State-of-the-art natural language processing
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Difference-aware knowledge selection for knowledge-grounded conversation generation
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KdConv: A Chinese multi-domain dialogue dataset towards multi-turn knowledge-driven conversation
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Survey on evaluation methods for dialogue systems
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Anticipating safety issues in e2e conversational ai: Framework and tooling
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Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A Smith, and Yejin Choi. 2022 · 2022
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Botstalk: Machine-sourced framework for automatic curation of large-scale multi-skill dialogue datasets
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On the safety of conversational models: Taxonomy, dataset, and benchmark
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Cdconv: A benchmark for contradiction detection in chinese conversations
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