Behnaz Soltani — accepted AI-conference papers

2025

Fine-Tuning Encoder-Decoder Models with Contrastive Learning for In-Context Distractor Generation

Elaf Alhazmi, Quan Z. Sheng, Wei Emma Zhang, Mohammed I. Thanoon, Haojie Zhuang, Behnaz Soltani +1

EMNLP 2025

Distractor generation is the task of automatically generating plausible yet incorrect options (i.e., distractors) for fill-in-the-blank and multiple-choice questions. In assessment, distractors must be contextually relevant to the given question and answer. Even though recent research works focus on

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2023

A Survey of Federated Evaluation in Federated Learning

Behnaz Soltani, Yipeng Zhou, Venus Haghighi, John C. S. Lui

IJCAI 2023poster

In traditional machine learning, it is trivial to conduct model evaluation since all data samples are managed centrally by a server. However, model evaluation becomes a challenging problem in federated learning (FL), which is called federated evaluation in this work. This is because clients do not e…

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