Papers by Mehrsa Mardikoraem
Calibrating LLM Confidence by Probing Perturbed Representation Stability (2025.emnlp-main)
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Reza Khanmohammadi, Erfan Miahi, Mehrsa Mardikoraem, Simerjot Kaur, Ivan Brugere, Charese Smiley, Kundan S Thind, Mohammad M. Ghassemi
| Challenge: | Despite their impressive performance, large language models (LLMs) consistently struggle with confidence calibration. |
| Approach: | They propose a method to analyze internal representational stability in large language models by applying adversarial perturbations to final hidden states and using a lightweight classifier to predict answer correctness. |
| Outcome: | CCPS significantly outperforms existing methods on LLMs from 8B to 32B parameters in multiple-choice and open-ended formats. |