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Found 3 papers, 2 papers with code
MTRec: Multi-Task Learning over BERT for News Recommendation
With the adoption of large pre-trained models like BERT in news recommendation, the above way to incorporate multi-field information may encounter challenges: the shallow feature encoding to compress the category and entity information is not compatible with the deep BERT encoding.
MINER: Multi-Interest Matching Network for News Recommendation
Accurately matching user’s interests and candidate news is the key to news recommendation.
Augmented Abstractive Summarization With Document-LevelSemantic Graph
Previous abstractive methods apply sequence-to-sequence structures to generate summary without a module to assist the system to detect vital mentions and relationships within a document.
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