对 MIND-small 上的神经新闻推荐系统 (NRMS) 进行虚假用户检测、防御和打击虚假用户行为的测试，并提供 Streamlit 评估演示。
A scalable two-stage news recommender that retrieves relevant candidates and reranks them using hybrid lexical and semantic features to optimize top-K recommendation quality.
Keras-based neural recommender system trained on the MIND dataset, using attention mechanisms and differentiable loss regularisation to balance accuracy, diversity, and novelty.
Explainable, diversity-aware offline feed ranking laboratory
A comparative study of recommender system strategies for news articles using the MIND dataset, focusing on both accuracy and beyond-accuracy metrics.
Interpretable hybrid news re-ranker on MIND-small with a leakage-audited evaluation protocol, nDCG@10 0.379 (write-up; source on request)
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