Distribution-Based Sensitivity Analysis (DBSA) is a lightweight, model-agnostic procedure designed to evaluate the sensitivity of a language model's output for each input token without requiring distributional assumptions about the language model.

Authors

• Person: Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche Organization: AISTATS
  Track: Poster Session 3 - aistats 2026

Sources

• Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS via serper

Referenced by nodes (1)

• Language Model concept