17 citations · 17 across the 8 of their papers we have counts for
4 papers · 1 filter
Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
Yoonah Park, Haesung Pyun, Yohan Jo
While large language models (LLMs) perform strongly on diverse tasks, their trustworthiness is limited by erratic behavior that is unfaithful to their internal knowledge. In partic…
Human Psychometric Questionnaires Mischaracterize LLM Behavior
Woojung Song, Dongmin Choi, Yoonah Park +3
We examine whether human psychometric questionnaires can serve as reliable tools for characterizing and predicting LLM behavior in everyday user interactions. We analyze eight open…
CUPID: Evaluating Personalized and Contextualized Alignment of LLMs from Interactions
Tae Soo Kim, Yoonjoo Lee, Yoonah Park +3
Personalization of Large Language Models (LLMs) often assumes users hold static preferences that reflect globally in all tasks. In reality, humans hold dynamic preferences that cha…
Improving Dialogue State Tracking through Combinatorial Search for In-Context Examples
Haesung Pyun, Yoonah Park, Yohan Jo
In dialogue state tracking (DST), in-context learning comprises a retriever that selects labeled dialogues as in-context examples and a DST model that uses these examples to infer…