Copertina

Automated Generation of Multiple-Choice Cloze Questions for Assessing English Vocabulary Using GPT-turbo 3.5

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Qiao, Rose, Ralph, Orita, Naho, Sugawara, Ayaka
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Constructing Cloze Questions Generatively
di: Sun, Yicheng, et al.
Pubblicazione: (2024)

Difficulty-Controllable Cloze Question Distractor Generation
di: Kang, Seokhoon, et al.
Pubblicazione: (2025)

Can GPT-3.5 Generate and Code Discharge Summaries?
di: Falis, Matúš, et al.
Pubblicazione: (2024)

Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions
di: Moore, Steven, et al.
Pubblicazione: (2024)

Automated Generation of Curriculum-Aligned Multiple-Choice Questions for Malaysian Secondary Mathematics Using Generative AI
di: Wahid, Rohaizah Abdul, et al.
Pubblicazione: (2025)

Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
di: Zhang, Yuhui, et al.
Pubblicazione: (2025)

Differentiating Choices via Commonality for Multiple-Choice Question Answering
di: Deng, Wenqing, et al.
Pubblicazione: (2024)

Anchored Answers: Unravelling Positional Bias in GPT-2's Multiple-Choice Questions
di: Li, Ruizhe, et al.
Pubblicazione: (2024)

Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal
di: Nair, Sathvik, et al.
Pubblicazione: (2026)

Multiple-Choice Questions are Efficient and Robust LLM Evaluators
di: Zhang, Ziyin, et al.
Pubblicazione: (2024)

Empowering Vocabulary Learning Through Teaching AI: Using LLMs as a Student to Perform Learning by Teaching in Vocabulary Acquisition
di: Uchida, Tokio, et al.
Pubblicazione: (2026)

Tell Me Who Your Students Are: GPT Can Generate Valid Multiple-Choice Questions When Students' (Mis)Understanding Is Hinted
di: Shimmei, Machi, et al.
Pubblicazione: (2025)

Multiple-Choice Question Generation Using Large Language Models: Methodology and Educator Insights
di: Biancini, Giorgio, et al.
Pubblicazione: (2025)

Difficulty-Controllable Multiple-Choice Question Generation Using Large Language Models and Direct Preference Optimization
di: Tomikawa, Yuto, et al.
Pubblicazione: (2025)

Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction
di: Lee, Yooseop, et al.
Pubblicazione: (2025)

UBench: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions
di: Wang, Xunzhi, et al.
Pubblicazione: (2024)

100% Elimination of Hallucinations on RAGTruth for GPT-4 and GPT-3.5 Turbo
di: Wood, Michael C., et al.
Pubblicazione: (2024)

Enhancing Clinical Multiple-Choice Questions Benchmarks with Knowledge Graph Guided Distractor Generation
di: Yang, Running, et al.
Pubblicazione: (2025)

Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
di: Lee, Jaewook, et al.
Pubblicazione: (2024)

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
di: Park, Yoonah, et al.
Pubblicazione: (2025)

Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?
di: Balepur, Nishant, et al.
Pubblicazione: (2024)

GPT-3.5 for Grammatical Error Correction
di: Katinskaia, Anisia, et al.
Pubblicazione: (2024)

HateGPT: Unleashing GPT-3.5 Turbo to Combat Hate Speech on X
di: Deroy, Aniket, et al.
Pubblicazione: (2024)

DisGeM: Distractor Generation for Multiple Choice Questions with Span Masking
di: Cavusoglu, Devrim, et al.
Pubblicazione: (2024)

Controlling Cloze-test Question Item Difficulty with PLM-based Surrogate Models for IRT Assessment
di: Zhang, Jingshen, et al.
Pubblicazione: (2024)

Enhancing Distractor Generation for Multiple-Choice Questions with Retrieval Augmented Pretraining and Knowledge Graph Integration
di: Yu, Han-Cheng, et al.
Pubblicazione: (2024)

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
di: Bsharat, Sondos Mahmoud, et al.
Pubblicazione: (2023)

Question Difficulty Ranking for Multiple-Choice Reading Comprehension
di: Raina, Vatsal, et al.
Pubblicazione: (2024)

LLM Distillation for Efficient Few-Shot Multiple Choice Question Answering
di: Sutanto, Patrick, et al.
Pubblicazione: (2024)

It is Too Many Options: Pitfalls of Multiple-Choice Questions in Generative AI and Medical Education
di: Singh, Shrutika, et al.
Pubblicazione: (2025)

Do Large Language Models Plan Answer Positions? Position Bias in Multiple-Choice Question Generation
di: Tang, Xuemei, et al.
Pubblicazione: (2026)

Evaluating the Symbol Binding Ability of Large Language Models for Multiple-Choice Questions in Vietnamese General Education
di: Nguyen, Duc-Vu, et al.
Pubblicazione: (2023)

Plausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning
di: Palta, Shramay, et al.
Pubblicazione: (2024)

Whose LLM is it Anyway? Linguistic Comparison and LLM Attribution for GPT-3.5, GPT-4 and Bard
di: Rosenfeld, Ariel, et al.
Pubblicazione: (2024)

UnibucLLM: Harnessing LLMs for Automated Prediction of Item Difficulty and Response Time for Multiple-Choice Questions
di: Rogoz, Ana-Cristina, et al.
Pubblicazione: (2024)

Polyglots or Multitudes? Multilingual LLM Answers to Value-laden Multiple-Choice Questions
di: Labat, Léo, et al.
Pubblicazione: (2026)

Rethinking Multiple-Choice Questions for RLVR: Unlocking Potential via Distractor Design
di: Guo, Xu, et al.
Pubblicazione: (2026)

Is GPT-4 Less Politically Biased than GPT-3.5? A Renewed Investigation of ChatGPT's Political Biases
di: Weber, Erik, et al.
Pubblicazione: (2024)

Biomedical Entity Linking as Multiple Choice Question Answering
di: Lin, Zhenxi, et al.
Pubblicazione: (2024)

Option-ID Based Elimination For Multiple Choice Questions
di: Zhu, Zhenhao, et al.
Pubblicazione: (2025)