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Calvin Bao

4 accepted papers

2025

Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations

EMNLP 2025

As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and

Cited by 0SourcePDFScholar
2025

Who’s the Author? How Explanations Impact User Reliance in AI-Assisted Authorship Attribution

EMNLP 2025

Despite growing interest in explainable NLP, it remains unclear how explanation strategies shape user behavior in tasks like authorship identification, where relevant textual features may be difficult for lay users to pinpoint. To support their analysis of text style, we consider two explanation typ

Cited by 0SourcePDFScholar
2024

Automatic Authorship Analysis in Human-AI Collaborative Writing

COLING 2024main

As the quality of AI-generated text increases with the development of new Large Language Models, people use them to write in a variety of contexts. Human-AI collaborative writing poses a potential challenge for existing AI analysis techniques, which have been primarily tested either on human-written…