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Explainable recommendation is a technique that combines prediction and generation tasks to produce more persuasive results.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Probabilistic matrix factorization
Ruslan Salakhutdinov and Andriy Mnih · 2007
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Factorization meets the neighborhood: a multifaceted collaborative filtering model
Yehuda Koren · 2008
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Long short-term memory
Alex Graves and Alex Graves · 2012
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Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
Yongfeng Zhang, Guokun Lai, and Shaoping Ma · 2014
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How should i explain? a comparison of different explanation types for recommender systems
Fatih Gedikli, Dietmar Jannach, and Mouzhi Ge · 2014
Earlier work this paper cites.
Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Explaining recommendations based on feature sentiments in product reviews
Li Chen and Feng Wang · 2017
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Neural rating regression with abstractive tips generation for recommendation
Piji Li, Zihao Wang, Zhaochun Ren, Lidong Bing, and Wai Lam · 2017
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Learning heterogeneous knowledge base embeddings for explainable recommendation
Qingyao Ai, Vahid Azizi, Xu Chen, and Yongfeng Zhang · 2018
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Explanation mining: Post hoc interpretability of latent factor models for recommendation systems
Georgina Peake and Jun Wang · 2018
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Neural attentional rating regression with review-level explanations
Chong Chen, Min Zhang, Yiqun Liu, and Shaoping Ma · 2018
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Co-attentive multi-task learning for explainable recommendation
Zhongxia Chen, Xiting Wang, Xing Xie, Tong Wu, Guoqing Bu, Yining Wang, and Enhong Chen · 2019
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Personalized fashion recommendation with visual explanations based on multimodal attention network: Towards visually explainable recommendation
Xu Chen, Hanxiong Chen, Hongteng Xu, Yongfeng Zhang, Yixin Cao, Zheng Qin, and Hongyuan Zha · 2019
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Reinforcement knowledge graph reasoning for explainable recommendation
Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, and Yongfeng Zhang · 2019
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Neural logic reasoning
Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang, and Yongfeng Zhang · 2020
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Pre-trained models for natural language processing: A survey
Xipeng Qiu, Tianxiang Sun, Yige Xu, Yunfan Shao, Ning Dai, and Xuanjing Huang · 2020
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Parade: Passage representation aggregation for document reranking
Canjia Li, Andrew Yates, Sean MacAvaney, Ben He, and Yingfei Sun · 2020
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Generate neural template explanations for recommendation
Lei Li, Yongfeng Zhang, and Li Chen · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Amanda, et al · 2020
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
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Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
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Generating long and informative reviews with aspect-aware coarse-to-fine decoding
Junyi Li, Wayne Xin Zhao, Ji-Rong Wen, and Yang Song · 2019
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, and Wen-tau Yih · 2020
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Hanxiong Chen, Xu Chen, Shaoyun Shi, and Yongfeng Zhang · 2021
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Personalized transformer for explainable recommendation
Lei Li, Yongfeng Zhang, and Li Chen · 2021
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Efficient passage retrieval with hashing for open-domain question answering
Ikuya Yamada, Akari Asai, and Hannaneh Hajishirzi · 2021
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Caesar: context-aware explanation based on supervised attention for service recommendations
Lei Li, Li Chen, and Ruihai Dong · 2021
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Rocketqav2: A joint training method for dense passage retrieval and passage re-ranking
Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qiaoqiao She, Hua Wu, Haifeng Wang, and Ji-Rong Wen · 2021
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Keybld: Selecting key blocks with local pre-ranking for long document information retrieval
Minghan Li and Eric Gaussier · 2021
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Rexplug: Explainable recommendation using plug-and-play language model
Deepesh V. Hada, Vijaikumar M, and Shirish K. Shevade · 2021
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Improving personalized explanation generation through visualization
Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo, and Yongfeng Zhang · 2022
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