Cover Image

Enhancing Clinical Multiple-Choice Questions Benchmarks with Knowledge Graph Guided Distractor Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Running, Deng, Wenlong, Chen, Minghui, Zhou, Yuyin, Li, Xiaoxiao
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective Distractors
by: Scaria, Nicy, et al.
Published: (2025)

Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation
by: Alhazmi, Elaf, et al.
Published: (2024)

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

Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning
by: McNichols, Hunter, et al.
Published: (2023)

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

Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
by: Feng, Wanyong, et al.
Published: (2024)

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

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

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models
by: Şakiroğlu, Mehmet Can, et al.
Published: (2026)

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

DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions
by: Fernandez, Nigel, et al.
Published: (2024)

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

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
by: Wu, Juncheng, et al.
Published: (2025)

PGDA-KGQA: A Prompt-Guided Generative Framework with Multiple Data Augmentation Strategies for Knowledge Graph Question Answering
by: Zhou, Xiujun, et al.
Published: (2025)

AraSTEM: A Native Arabic Multiple Choice Question Benchmark for Evaluating LLMs Knowledge In STEM Subjects
by: Mustapha, Ahmad, et al.
Published: (2024)

DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models
by: Deng, Wenlong, et al.
Published: (2024)

Applying Relation Extraction and Graph Matching to Answering Multiple Choice Questions
by: Shimoda, Naoki, et al.
Published: (2025)

Correctness Coverage Evaluation for Medical Multiple-Choice Question Answering Based on the Enhanced Conformal Prediction Framework
by: Ke, Yusong, et al.
Published: (2025)

Pattern Recognition or Medical Knowledge? The Problem with Multiple-Choice Questions in Medicine
by: Griot, Maxime, et al.
Published: (2024)

For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs
by: Deng, Wenlong, et al.
Published: (2025)

More Bias, Less Bias: BiasPrompting for Enhanced Multiple-Choice Question Answering
by: Vu, Duc Anh, et al.
Published: (2025)

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

MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback
by: Yao, Zonghai, et al.
Published: (2024)

Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
by: Liu, Haochen, et al.
Published: (2025)

Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction
by: Wu, Tao, et al.
Published: (2025)

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

Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering
by: Zhang, Yu, et al.
Published: (2024)

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

Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering
by: Jiang, Longquan, et al.
Published: (2025)

Hierarchical Vision-Language Reasoning for Multimodal Multiple-Choice Question Answering
by: Zhou, Ao, et al.
Published: (2025)

KNIGHT: Knowledge Graph-Driven Multiple-Choice Question Generation with Adaptive Hardness Calibration
by: Amanlou, Mohammad, et al.
Published: (2026)

SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions
by: Xu, Weijie, et al.
Published: (2025)

†DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
by: Nazi, Zabir Al, et al.
Published: (2026)

MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering
by: Li, Feiyang, et al.
Published: (2025)

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

CLEAR-KGQA: Clarification-Enhanced Ambiguity Resolution for Knowledge Graph Question Answering
by: Wen, Liqiang, et al.
Published: (2025)