Xinyi Ding — accepted AI-conference papers

2025

Mixture of Experts Based Multi-Task Supervise Learning from Crowds

Tao Han, Huaixuan Shi, Xinyi Ding, Xi-Ao Ma, Huamao Gu, Yili Fang

AAAI 2025technical

Existing learning-from-crowds methods aim to design proper aggregation strategies to infer the unknown true labels from noisy labels provided by crowdsourcing. They treat the ground truth as hidden variables and use statistical or deep learning based worker behavior models to infer the ground truth.…

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2023

TDG4Crowd:Test Data Generation for Evaluation of Aggregation Algorithms in Crowdsourcing

Yili Fang, Chaojie Shen, Huamao Gu, Tao Han, Xinyi Ding

IJCAI 2023poster

In crowdsourcing, existing efforts mainly use real datasets collected from crowdsourcing as test datasets to evaluate the effectiveness of aggregation algorithms. However, these work ignore the fact that the datasets obtained by crowdsourcing are usually sparse and imbalanced due to limited budget.…

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