I’m excited to share two papers that will be presented at EMNLP 2026 in Budapest later this month, on user simulation and natural language user profiles.
- “Act Like a 5th Grader” is Not Enough: Bounding Knowledge in LLM-Based User Simulators (Findings paper, with A. M. Bakken) — LLM-based simulators tend to be “superhuman”: even when prompted to act like a 5th grader, they ace reading comprehension tests. Using over 71k responses from 2,359 Norwegian primary-school students, we propose the Cognitively Bounded User Simulator (CBUS), which models restricted working memory through an episodic bottleneck and substantially reduces the gap to real student behavior.
- A Survey on Natural Language User Profiles for Recommendation: Methods, Datasets, and Metrics (main conference paper, with M. Arustashvili) — This survey reviews the literature on the two coupled tasks of profile generation and profile-based recommendation, proposes a taxonomy for organizing evaluation metrics, and outlines open challenges, including the tension between transparency and optimization.
I’ll be attending the conference in person. If you’re there, please come say hello!