(WhyPHI) Fine-Tuning PHI-3 for Multiple-Choice Question Answering: Methodology, Results, and Challenges
Fuente:
arXiv
Saved in:
| Main Author: | Abdellatif, Mohamed Hisham |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
RAD-PHI2: Instruction Tuning PHI-2 for Radiology
by: Ranjit, Mercy, et al.
Published: (2024)
by: Ranjit, Mercy, et al.
Published: (2024)
LLMs-in-the-Loop Part 2: Expert Small AI Models for Anonymization and De-identification of PHI Across Multiple Languages
by: Gunay, Murat, et al.
Published: (2024)
by: Gunay, Murat, et al.
Published: (2024)
Differentiating Choices via Commonality for Multiple-Choice Question Answering
by: Deng, Wenqing, et al.
Published: (2024)
by: Deng, Wenqing, et al.
Published: (2024)
MuPHI: Learning Implicit Multimodal Harm Reasoning via Semantically Grounded Reward Optimization
by: Saha, Anisha, et al.
Published: (2026)
by: Saha, Anisha, et al.
Published: (2026)
Biomedical Entity Linking as Multiple Choice Question Answering
by: Lin, Zhenxi, et al.
Published: (2024)
by: Lin, Zhenxi, et al.
Published: (2024)
Assessment of RAG and Fine-Tuning for Industrial Question-Answering-Applications
by: Sturm, Jakob, et al.
Published: (2026)
by: Sturm, Jakob, et al.
Published: (2026)
Fine-Tuning LLMs for Reliable Medical Question-Answering Services
by: Anaissi, Ali, et al.
Published: (2024)
by: Anaissi, Ali, et al.
Published: (2024)
Conformal P-Value in Multiple-Choice Question Answering Tasks with Provable Risk Control
by: Ye, Yuanchang
Published: (2025)
by: Ye, Yuanchang
Published: (2025)
Question Answering on Patient Medical Records with Private Fine-Tuned LLMs
by: Kothari, Sara, et al.
Published: (2025)
by: Kothari, Sara, et al.
Published: (2025)
60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering
by: Ye, Junjie, et al.
Published: (2024)
by: Ye, Junjie, et al.
Published: (2024)
Multiple-Choice Question Generation Using Large Language Models: Methodology and Educator Insights
by: Biancini, Giorgio, et al.
Published: (2025)
by: Biancini, Giorgio, et al.
Published: (2025)
A Study on Large Language Models' Limitations in Multiple-Choice Question Answering
by: Khatun, Aisha, et al.
Published: (2024)
by: Khatun, Aisha, et al.
Published: (2024)
Conformal Sets in Multiple-Choice Question Answering under Black-Box Settings with Provable Coverage Guarantees
by: Yang, Guang, et al.
Published: (2025)
by: Yang, Guang, et al.
Published: (2025)
PHI-S: Distribution Balancing for Label-Free Multi-Teacher Distillation
by: Ranzinger, Mike, et al.
Published: (2024)
by: Ranzinger, Mike, et al.
Published: (2024)
Fine-Tuning BERT for Domain-Specific Question Answering: Toward Educational NLP Resources at University Scale
by: Montfrond, Aurélie
Published: (2025)
by: Montfrond, Aurélie
Published: (2025)
Parameter Efficient Fine Tuning Llama 3.1 for Answering Arabic Legal Questions: A Case Study on Jordanian Laws
by: Fasha, Mohammed, et al.
Published: (2026)
by: Fasha, Mohammed, et al.
Published: (2026)
Question Difficulty Ranking for Multiple-Choice Reading Comprehension
by: Raina, Vatsal, et al.
Published: (2024)
by: Raina, Vatsal, et al.
Published: (2024)
Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology
by: Tran, Son Quoc, et al.
Published: (2024)
by: Tran, Son Quoc, et al.
Published: (2024)
Plausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning
by: Palta, Shramay, et al.
Published: (2024)
by: Palta, Shramay, et al.
Published: (2024)
Answering Questions by Meta-Reasoning over Multiple Chains of Thought
by: Yoran, Ori, et al.
Published: (2023)
by: Yoran, Ori, et al.
Published: (2023)
Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions
by: Moore, Steven, et al.
Published: (2024)
by: Moore, Steven, et al.
Published: (2024)
Collaboration among Multiple Large Language Models for Medical Question Answering
by: Shang, Kexin, et al.
Published: (2025)
by: Shang, Kexin, et al.
Published: (2025)
A Dataset of Open-Domain Question Answering with Multiple-Span Answers
by: Luo, Zhiyi, et al.
Published: (2024)
by: Luo, Zhiyi, et al.
Published: (2024)
MedExQA: Medical Question Answering Benchmark with Multiple Explanations
by: Kim, Yunsoo, et al.
Published: (2024)
by: Kim, Yunsoo, et al.
Published: (2024)
Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
by: Hassan, Tasnimul, et al.
Published: (2025)
by: Hassan, Tasnimul, et al.
Published: (2025)
Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction
by: Lee, Yooseop, et al.
Published: (2025)
by: Lee, Yooseop, et al.
Published: (2025)
Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions
by: Wiegreffe, Sarah, et al.
Published: (2024)
by: Wiegreffe, Sarah, et al.
Published: (2024)
Option-ID Based Elimination For Multiple Choice Questions
by: Zhu, Zhenhao, et al.
Published: (2025)
by: Zhu, Zhenhao, et al.
Published: (2025)
pdfQA: Diverse, Challenging, and Realistic Question Answering over PDFs
by: Schimanski, Tobias, et al.
Published: (2026)
by: Schimanski, Tobias, et al.
Published: (2026)
Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question Answering
by: Li, Gang, et al.
Published: (2025)
by: Li, Gang, et al.
Published: (2025)
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
by: Zhang, Yuhui, et al.
Published: (2025)
by: Zhang, Yuhui, et al.
Published: (2025)
Balancing Rigor and Utility: Mitigating Cognitive Biases in Large Language Models for Multiple-Choice Questions
by: Zhong, Hanyang, et al.
Published: (2024)
by: Zhong, Hanyang, et al.
Published: (2024)
Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
by: Bao, Qiming, et al.
Published: (2023)
by: Bao, Qiming, et al.
Published: (2023)
It is Too Many Options: Pitfalls of Multiple-Choice Questions in Generative AI and Medical Education
by: Singh, Shrutika, et al.
Published: (2025)
by: Singh, Shrutika, et al.
Published: (2025)
QU-NLP at ArchEHR-QA 2026: Two-Stage QLoRA Fine-Tuning of Qwen3-4B for Patient-Oriented Clinical Question Answering and Evidence Sentence Alignment
by: AL-Smadi, Mohammad
Published: (2026)
by: AL-Smadi, Mohammad
Published: (2026)
Towards Locally Deployable Fine-Tuned Causal Large Language Models for Mode Choice Behaviour
by: Alsaleh, Tareq, et al.
Published: (2025)
by: Alsaleh, Tareq, et al.
Published: (2025)
Pattern Recognition or Medical Knowledge? The Problem with Multiple-Choice Questions in Medicine
by: Griot, Maxime, et al.
Published: (2024)
by: Griot, Maxime, et al.
Published: (2024)
Choices Speak Louder than Questions
by: Cho, Gyeongje, et al.
Published: (2025)
by: Cho, Gyeongje, et al.
Published: (2025)
Fine-tuning Multi-hop Question Answering with Hierarchical Graph Network
by: Xiong, Guanming
Published: (2020)
by: Xiong, Guanming
Published: (2020)
Automated Generation of Curriculum-Aligned Multiple-Choice Questions for Malaysian Secondary Mathematics Using Generative AI
by: Wahid, Rohaizah Abdul, et al.
Published: (2025)
by: Wahid, Rohaizah Abdul, et al.
Published: (2025)
Similar Items
-
RAD-PHI2: Instruction Tuning PHI-2 for Radiology
by: Ranjit, Mercy, et al.
Published: (2024) -
LLMs-in-the-Loop Part 2: Expert Small AI Models for Anonymization and De-identification of PHI Across Multiple Languages
by: Gunay, Murat, et al.
Published: (2024) -
Differentiating Choices via Commonality for Multiple-Choice Question Answering
by: Deng, Wenqing, et al.
Published: (2024) -
MuPHI: Learning Implicit Multimodal Harm Reasoning via Semantically Grounded Reward Optimization
by: Saha, Anisha, et al.
Published: (2026) -
Biomedical Entity Linking as Multiple Choice Question Answering
by: Lin, Zhenxi, et al.
Published: (2024)