arXiv AI By Krisztian Balog, Arild Michel Bakken

"Act Like a 5th Grader" is Not Enough: Bounding Knowledge in LLM-Based User Simulators

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arXiv AI
Aug 19

KnowSim: Evaluating Information Calibration in LLM Assistants with User Simulators that Learn

KnowSim introduces an evaluation framework that uses a user simulator with explicit knowledge states to assess how well large language models calibrate information to users. The simulator represents knowledge as a graph of Information Units with prerequisite relationships and updates these states based on learning theory. KnowSim computes Knowledge Gain, Delivery Calibration, and Cognitive Overload metrics, and its rankings align with human judgments, outperforming baseline simulators and revealing model performance differences across user knowledge levels.

By Yoonjoo Lee, Hyoungwook Jin, Tae Soo Kim, Shaoyang Zhang, Philippe Laban, Q. Vera Liao
arXiv AI
Jul 24

AI Assistants Overassist

arXiv:2607. 21306v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems.

By Verona Teo, Raghav Jain, Tobias Gerstenberg, Max Kleiman-Weiner