Elaf Alhazmi — 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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2024

Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation

Elaf Alhazmi, Quan Z. Sheng, Wei Emma Zhang, Munazza Zaib, Ahoud Alhazmi

EMNLP 2024main

The distractor generation task focuses on generating incorrect but plausible options for objective questions such as fill-in-the-blank and multiple-choice questions. This task is widely utilized in educational settings across various domains and subjects. The effectiveness of these questions in asse…

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