Papers by Zhaopeng Qiu

3 papers
Automatic Distractor Generation for Multiple Choice Questions in Standard Tests (2020.coling-main)

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Challenge: Existing methods to generate distractors for multiple choice questions are expensive and time-consuming.
Approach: They propose a question and answer guided distractor generation framework to automate distractors generated by domain experts.
Outcome: The proposed model outperforms existing models and achieves state-of-the-art on a large-scale dataset.
DeltaNet: Conditional Medical Report Generation for COVID-19 Diagnosis (2022.coling-1)

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Challenge: X-ray and CT are the gold standard for COVID-19 diagnosis and treatment . however, due to the excessive number of patients, writing reports becomes a heavy burden for radiologists.
Approach: They propose to use X-ray and CT to generate medical reports automatically . they evaluate DeltaNet on a COVID-19 dataset, where it outperforms state-of-the-art approaches .
Outcome: The proposed system outperforms state-of-the-art methods on a COVID-19 dataset.
Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback (2022.findings-naacl)

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Challenge: Existing work on news recommendation only used positive and negative implicit feedback and suffered from the noise impact.
Approach: They propose a denoising neural network for news recommendation with positive and negative implicit feedback, named DRPN.
Outcome: The proposed method improves on the real-world large-scale dataset.

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