325 citations · 400 across the 19 of their papers we have counts for
3 papers · 1 filter
AI Annotation Orchestration: Evaluating LLM verifiers to Improve the Quality of LLM Annotations in Learning Analytics
Bakhtawar Ahtisham, Kirk Vanacore, Jinsook Lee +3
Large Language Models (LLMs) are increasingly used to annotate learning interactions, yet concerns about reliability limit their utility. We test whether verification-oriented orch…
When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts
Chengyuan Yao, Yunxuan Tang, Christopher Brooks +2
Predictive models are typically trained on historical data to predict future outcomes. While it is commonly assumed that training on more historical data would improve model perfor…
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…