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Found 4 papers, 1 papers with code
Opportunities for Human-centered Evaluation of Machine Translation Systems
Machine translation models are embedded in larger user-facing systems.
Angler: Helping Machine Translation Practitioners Prioritize Model Improvements
Machine learning (ML) models can fail in unexpected ways in the real world, but not all model failures are equal.
Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trust
Machine Translation (MT) has the potential to help people overcome language barriers and is widely used in high-stakes scenarios, such as in hospitals.
What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design
Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholder preferences to create algorithmic systems that account for those stakeholders' values.
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