Summary of Differentiating Choices Via Commonality For Multiple-choice Question Answering, by Wenqing Deng et al.
Differentiating Choices via Commonality for Multiple-Choice Question Answering
by Wenqing Deng, Zhe Wang, Kewen Wang, Shirui Pan, Xiaowang Zhang, Zhiyong Feng
First submitted to arxiv on: 21 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel multiple-choice question answering (MCQA) model called DCQA, which leverages semantic commonalities and nuances among choices for reasoning. Existing models often overlook context provided by other choices, whereas DCQA captures token-level attention of each choice to the question and separates tokens attended to by all choices from those attended to by individual choices. This allows DCQA to effectively differentiate choices with subtle differences and provide justifications for choosing the correct answer. The paper conducts comprehensive experiments across five MCQA benchmarks, demonstrating that DCQA consistently outperforms baseline models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps machines better understand multiple-choice questions. Right now, most computers rank each choice separately without considering what other options have in common. This makes it hard to choose the right answer. The researchers came up with a new way for computers to do MCQA by looking at how all the choices relate to each other. They call this approach DCQA (differentiating choices through identifying and eliminating their commonality). This new method is better than existing methods because it can recognize tiny differences between options and explain why one option is correct. |
Keywords
» Artificial intelligence » Attention » Question answering » Token
