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Atiyeh Ashari Ghomi

2 accepted papers

2026

Textual Bayes: Quantifying Uncertainty in LLM-Based Systems

ICLR 2026poster

Although large language models (LLMs) are becoming increasingly capable of solving challenging real-world tasks, accurately quantifying their uncertainty remains a critical open problem—one that limits their applicability in high-stakes domains. This challenge is further compounded by the closed-sou…

Cited by 0SourcecodeScholar
2023

Disparate Impact in Differential Privacy from Gradient Misalignment

ICLR 2023top-25%

As machine learning becomes more widespread throughout society, aspects including data privacy and fairness must be carefully considered, and are crucial for deployment in highly regulated industries. Unfortunately, the application of privacy enhancing technologies can worsen unfair tendencies in mo…