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1
NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Better ...
Wu, Chuhan; Wu, Fangzhao; Qi, Tao. - : arXiv, 2022
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2
Empowering News Recommendation with Pre-trained Language Models ...
Wu, Chuhan; Wu, Fangzhao; Qi, Tao. - : arXiv, 2021
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3
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation ...
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4
One Teacher is Enough? Pre-trained Language Model Distillation from Multiple Teachers ...
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5
Hi-Transformer: Hierarchical Interactive Transformer for Efficient and Effective Long Document Modeling ...
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6
One Teacher is Enough? Pre-trained Language Model Distillation from Multiple Teachers ...
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7
HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation ...
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8
PP-Rec: News Recommendation with Personalized User Interest and Time-aware News Popularity ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.424 Abstract: Personalized news recommendation methods are widely used in online news services. These methods usually recommend news based on the matching between news content and user interest inferred from historical behaviors. However, these methods usually have difficulties in making accurate recommendations to cold-start users, and tend to recommend similar news with those users have read. In general, popular news usually contain important information and can attract users with different interests. Besides, they are usually diverse in content and topic. Thus, in this paper we propose to incorporate news popularity information to alleviate the cold-start and diversity problems for personalized news recommendation. In our method, the ranking score for recommending a candidate news to a target user is the combination of a personalized matching score and a news popularity score. The former is used to capture the personalized user interest in news. The ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25851-pp-rec-news-recommendation-with-personalized-user-interest-and-time-aware-news-popularity
https://dx.doi.org/10.48448/bmam-tr65
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9
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark ...
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10
Neural news recommendation with negative feedback [<Journal>]
Wu, Chuhan [Verfasser]; Wu, Fangzhao [Verfasser]; Huang, Yongfeng [Verfasser].
DNB Subject Category Language
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11
Helpfulness-aware review based neural recommendation [<Journal>]
Ge, Suyu [Verfasser]; Qi, Tao [Verfasser]; Wu, Chuhan [Verfasser].
DNB Subject Category Language
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12
Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization ...
Liu, Junxin; Wu, Fangzhao; Wu, Chuhan. - : arXiv, 2019
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