SOTAVerified

Multiple Choice Question Answering (MCQA)

A multiple-choice question (MCQ) is composed of two parts: a stem that identifies the question or problem, and a set of alternatives or possible answers that contain a key that is the best answer to the question, and a number of distractors that are plausible but incorrect answers to the question.

In a k-way MCQA task, a model is provided with a question q, a set of candidate options O = {O1, . . . , Ok}, and a supporting context for each option C = {C1, . . . , Ck}. The model needs to predict the correct answer option that is best supported by the given contexts.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 65 papers

TitleStatusHype
Context-guided Triple Matching for Multiple Choice Question Answering—0
Context-guided Triple Matching for Multiple Choice Question Answering—0
Context Modeling with Evidence Filter for Multiple Choice Question Answering—0
Correctness Coverage Evaluation for Medical Multiple-Choice Question Answering Based on the Enhanced Conformal Prediction Framework—0
CP-Router: An Uncertainty-Aware Router Between LLM and LRM—0
Fine-tuning BERT with Focus Words for Explanation Regeneration—0
Disaggregating Hops: Can We Guide a Multi-Hop Reasoning Language Model to Incrementally Learn at each Hop?—0
KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations—0
Transliteration: A Simple Technique For Improving Multilingual Language Modeling—0
Evaluating the Symbol Binding Ability of Large Language Models for Multiple-Choice Questions in Vietnamese General Education—0
First Token Probability Guided RAG for Telecom Question Answering—0
Unsupervised multiple choices question answering via universal corpus—0
Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above—0
BloombergGPT: A Large Language Model for Finance—0
LLM Distillation for Efficient Few-Shot Multiple Choice Question Answering—0
Visual7W: Grounded Question Answering in Images—0
Generating multiple-choice questions for medical question answering with distractors and cue-masking—0
BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine—0
LLMs May Perform MCQA by Selecting the Least Incorrect Option—0
Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning—0
Healthy LLMs? Benchmarking LLM Knowledge of UK Government Public Health Information—0
Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering—0
HRCA+: Advanced Multiple-choice Machine Reading Comprehension Method—0
What do we expect from Multiple-choice QA Systems?—0
Improving LLM First-Token Predictions in Multiple-Choice Question Answering via Prefilling Attack—0
Show:102550
← PrevPage 2 of 3Next →

No leaderboard results yet.