Digory Smith — accepted AI-conference papers

2025

PIIvot: A Lightweight NLP Anonymization Framework for Question-Anchored Tutoring Dialogues

Matthew Zent, Digory Smith, Simon Woodhead

EMNLP 2025

Personally identifiable information (PII) anonymization is a high-stakes task that poses a barrier to many open-science data sharing initiatives. While PII identification has made large strides in recent years, in practice, error thresholds and the recall/precision trade-off still limit the uptake o

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2024

Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models

Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead +2

NAACL 2024findings

Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common…

Cited by 18 Source ↗PDF ↗code ↗Scholar ↗