325 citations · 400 across the 19 of their papers we have counts for
6 papers · 1 filter
LLM Reasoning Predicts When Models Are Right: Evidence from Coding Classroom Discourse
Bakhtawar Ahtisham, Kirk Vanacore, Zhuqian Zhou +2
Large Language Models (LLMs) are increasingly deployed to automatically label and analyze educational dialogue at scale, yet current pipelines lack reliable ways to detect when mod…
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…
Codebook-Injected Dialogue Segmentation for Multi-Utterance Constructs Annotation: LLM-Assisted and Gold-Label-Free Evaluation
Jinsook Lee, Kirk Vanacore, Zhuqian Zhou +3
Dialogue Act (DA) annotation typically treats communicative or pedagogical intent as localized to individual utterances or turns. This leads annotators to agree on the underlying a…
Poor Alignment and Steerability of Large Language Models: Evidence from College Admission Essays
Jinsook Lee, AJ Alvero, Thorsten Joachims +1
People are increasingly using technologies equipped with large language models (LLM) to write texts for formal communication, which raises two important questions at the intersecti…
Cultural Bias and Cultural Alignment of Large Language Models
Yan Tao, Olga Viberg, Ryan S. Baker +1
Culture fundamentally shapes people's reasoning, behavior, and communication. As people increasingly use generative artificial intelligence (AI) to expedite and automate personal a…
Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters
Jinsook Lee, Bradon Thymes, Joyce Zhou +2
University admission at many highly selective institutions uses a holistic review process, where all aspects of the application, including protected attributes (e.g., race, gender)…