collaborators

12 papers

cs.CL2026

Redact or Keep? A Fully Local AI Cascade for Educational Dialogue De-Identification

Haocheng Zhang, Zhuqian Zhou, Kirk Vanacore +2

Educational dialogue is a valuable but sensitive resource for research: the same transcripts that capture authentic learning often capture personally identifiable information (PII)…

cs.CL2026

Utility-Preserving De-Identification for Math Tutoring: Investigating Numeric Ambiguity in the MathEd-PII Benchmark Dataset

Zhuqian Zhou, Kirk Vanacore, Bakhtawar Ahtisham +7

Large-scale sharing of dialogue data is key to advancing the science of teaching and learning, yet rigorous de-identification remains a major barrier. In mathematics tutoring trans…

cs.HC2026

Sandpiper: Orchestrated AI-Annotation for Educational Discourse at Scale

Daryl Hedley, Doug Pietrzak, Jorge Dias +9

Digital educational environments are expanding toward complex AI and human discourse, providing researchers with an abundance of data that offers deep insights into learning and in…

cs.CY2026

Million Tutoring Moves (MTM): An Open Multimodal Dataset for the Science of Tutoring

René Kizilcec, Kirk Vanacore, Zhuqian Zhou +8

We introduce the Million Tutoring Moves (MTM) project, an open dataset initiative aimed at advancing the science of tutoring through large-scale, reusable, and multimodal interacti…

cs.CL2026

Domain-Adapted Retrieval for In-Context Annotation of Pedagogical Dialogue Acts

Jinsook Lee, Kirk Vanacore, Zhuqian Zhou +2

Automated annotation of pedagogical dialogue is a high-stakes task where LLMs often fail without sufficient domain grounding. We present a domain-adapted RAG pipeline for tutoring…

cs.CR2026

Can You Tell It's AI? Human Perception of Synthetic Voices in Vishing Scenarios

Zoha Hayat Bhatti, Bakhtawar Ahtisham, Seemal Tausif +3

Large Language Models and commercial speech synthesis systems now enable highly realistic AI-generated voice scams (vishing), raising urgent concerns about deception at scale. Yet…