3 papers
cs.CL2026
Beyond Fine-Tuning: In-Context Learning and Chain-of-Thought for Reasoned Distractor Generation
Elaf Alhazmi, Quan Z. Sheng, Wei Emma Zhang
Distractor generation (DG) remains a labor-intensive task that still significantly depends on domain experts. The task focuses on generating plausible yet incorrect options, known…
cs.CL2026
From Instruction to Output: The Role of Prompting in Modern NLG
Munazza Zaib, Elaf Alhazmi
Prompt engineering has emerged as an integral technique for extending the strengths and abilities of Large Language Models (LLMs) to gain significant performance gains in various N…
cs.CL2024
Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation
Elaf Alhazmi, Quan Z. Sheng, Wei Emma Zhang +2
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 w…