mlsanityData to 7 Oct 2026

Clues Before Answers: Generation-Enhanced Multiple-Choice QA

arXiv 2205.00274 ↗First posted 30 Apr 2022cs.CLcited by 9

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Abstract (arXiv)

A trending paradigm for multiple-choice question answering (MCQA) is using a text-to-text framework. By unifying data in different tasks into a single text-to-text format, it trains a generative encoder-decoder model which is both powerful and universal. However, a side effect of twisting a generation target to fit the classification nature of MCQA is the under-utilization of the decoder and the knowledge that can be decoded. To exploit the generation capability and underlying knowledge of a pre-trained encoder-decoder model, in this paper, we propose a generation-enhanced MCQA model named GenMC. It generates a clue from the question and then leverages the clue to enhance a reader for MCQA. It outperforms text-to-text models on multiple MCQA datasets.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 34 of its 47 references that are in the map. First posted on arXiv 30 Apr 2022.

Builds on

34 of 47 references.

References · 34

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22 more
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Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 3; 2024: 4; 2025: 1.

9 papers.

  1. 2023KnowGPT: Knowledge Graph based Prompting for Large Language Modelscited by 30
  2. 2022Elaboration-Generating Commonsense Question Answering at Scalecited by 9
  3. 2023Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answeringcited by 6
  4. 2024XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generationcited by 3
  5. 2024PipeNet: Question Answering with Semantic Pruning over Knowledge Graphscited by 1
  6. 2025Pipelined Decoder for Efficient Context-Aware Text Generationcited by 1
  7. 2023Scaling Pre-trained Language Models to Deeper via Parameter-efficient Architecturecited by 0
  8. 2024Differentiating Choices via Commonality for Multiple-Choice Question Answeringcited by 0
  9. 2024Internal and External Knowledge Interactive Refinement Framework for Knowledge-Intensive Question Answeringcited by 0