← Search

Nastaran Okati

7 accepted papers

2026

Is Your LLM Overcharging You? Tokenization, Transparency, and Incentives

ICML 2026oral

State-of-the-art large language models require specialized hardware and substantial energy to operate. Consequently, cloud-based services that provide access to these models have become very popular. In these services, the price users pay depends on the number of tokens a model uses to generate an o…

Cited by 0SourcecodeScholar
2025

Root Cause Analysis of Outliers with Missing Structural Knowledge

NeurIPS 2025poster

The goal of Root Cause Analysis (RCA) is to explain why an anomaly occurred by identifying where the fault originated. Several recent works model the anomalous event as resulting from a change in the causal mechanism at the root cause, i.e., as a soft intervention. RCA is then the task of identifyin…

Cited by 0SourceScholar
2024

Towards Human-AI Complementarity with Prediction Sets

NeurIPS 2024poster

Decision support systems based on prediction sets have proven to be effective at helping human experts solve classification tasks. Rather than providing single-label predictions, these systems provide sets of label predictions constructed using conformal prediction, namely prediction sets, and ask h…

2023

Improving Expert Predictions with Conformal Prediction

ICML 2023poster

Automated decision support systems promise to help human experts solve multiclass classification tasks more efficiently and accurately. However, existing systems typically require experts to understand when to cede agency to the system or when to exercise their own agency. Otherwise, the experts may…

2023

On the Within-Group Fairness of Screening Classifiers

ICML 2023poster

Screening classifiers are increasingly used to identify qualified candidates in a variety of selection processes. In this context, it has been recently shown that if a classifier is calibrated, one can identify the smallest set of candidates which contains, in expectation, a desired number of qualif…