Among 919 intro CS students solving Prompt Problems, typed prompts beat unedited voice on first-attempt success for two of three tasks; edited voice matched text, and most preferred text.
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Zero-shot vision-language models are unreliable and vary widely for depression screening, and explainability-based fairness interventions often trade away accuracy without reliable fairness gains.
citing papers explorer
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Say What? Examining Text and Voice Input Modalities for Prompt-Based Programming in Computing Education
Among 919 intro CS students solving Prompt Problems, typed prompts beat unedited voice on first-attempt success for two of three tasks; edited voice matched text, and most preferred text.
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FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment
Zero-shot vision-language models are unreliable and vary widely for depression screening, and explainability-based fairness interventions often trade away accuracy without reliable fairness gains.