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News recommendation is a widely adopted technique to provide personalized news feeds for the user.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Embedding-Based News Recommendation for Millions of Users
Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima. 2017 · 1942
Earlier work this paper cites.
Google News Personalization: Scalable Online Collaborative Filtering
Abhinandan S. Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram. 2007 · 2007
Earlier work this paper cites.
User Attitudes towards News Content Personalization
Talia Lavie, Michal Sela, Ilit Oppenheim, Ohad Inbar, and Joachim Meyer. 2010 · 2010
Earlier work this paper cites.
Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Universal Language Model Fine-tuning for Text Classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Earlier work this paper cites.
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Earlier work this paper cites.
DKN: Deep Knowledge-Aware Network for News Recommendation
Hongwei Wang, Fuzheng Zhang, Xing Xie, and Minyi Guo. 2018 · 2018
Earlier work this paper cites.
SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
Earlier work this paper cites.
IMHO Fine-Tuning Improves Claim Detection
Tuhin Chakrabarty, Christopher Hidey, and Kathy McKeown. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings
Kawin Ethayarajh. 2019 · 2019
Cited alongside, same era.
Representation Degeneration Problem in Training Natural Language Generation Models
Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tie-Yan Liu. 2019 · 2019
Cited alongside, same era.
Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling
Xiaochuang Han and Jacob Eisenstein. 2019 · 2019
Cited alongside, same era.
BioBERT: A Pre-trained Biomedical Language Representation Model for Biomedical Text Mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019 · 2019
Cited alongside, same era.
TinyBERT: Distilling BERT for Natural Language Understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020 · 2020
Later among the works it cites.
Adaptive Multi-Teacher Multi-level Knowledge Distillation
Yuang Liu, Wei Zhang, and Jun Wang. 2020 · 2020
Later among the works it cites.
TwinBERT: Distilling Knowledge to Twin-Structured Compressed BERT Models for Large-Scale Retrieval
Wenhao Lu, Jian Jiao, and Ruofei Zhang. 2020 · 2020
Later among the works it cites.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Later among the works it cites.
MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, and Denny Zhou. 2020 · 2020
Later among the works it cites.
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Zero-Shot Entity Linking by Reading Entity Descriptions
Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, and Honglak Lee. 2019 · 2019
Cited alongside, same era.
Patient Knowledge Distillation for BERT Model Compression
Siqi Sun, Yu Cheng, Zhe Gan, and Jingjing Liu. 2019 · 2019
Cited alongside, same era.
DAN: Deep Attention Neural Network for News Recommendation
Qiannan Zhu, Xiaofei Zhou, Zeliang Song, Jianlong Tan, and Li Guo. 2019 · 2019
Cited alongside, same era.
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, and Hsiao-Wuen Hon. 2020 · 2020
Cited alongside, same era.
Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
Cited alongside, same era.
Graph Neural News Recommendation with Long-term and Short-term Interest Modeling
Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, and Chao Shao. 2020 · 2020
Cited alongside, same era.
On the Sentence Embeddings from Pre-trained Language Models
Bohan Li, Hao Zhou, Junxian He, Mingxuan Wang, Yiming Yang, and Lei Li. 2020a
Cited in the paper.
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020 · 2020
Later among the works it cites.
MIND: A Large-scale Dataset for News Recommendation
Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, and Ming Zhou. 2020 · 2020
Later among the works it cites.
BERT-of-Theseus: Compressing BERT by Progressive Module Replacing
Canwen Xu, Wangchunshu Zhou, Tao Ge, Furu Wei, and Ming Zhou. 2020 · 2020
Later among the works it cites.
RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT
Qinglin Jia, Jingjie Li, Qi Zhang, Xiuqiang He, and Jieming Zhu. 2021 · 2021
Closest in time.
TADPOLE: Task ADapted Pre-Training via AnOmaLy DEtection
Vivek Madan, Ashish Khetan, and Zohar Karnin. 2021 · 2021
Closest in time.