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Recent models can generate fluent and grammatical synthetic reviews while accurately predicting user ratings.
On Faithfulness and Factuality in Abstractive Summarization
Maynez, J.; Narayan, S.; Bohnet, B.; and McDonald, R. 2020 · 1919
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Unsupervised Opinion Summarization with Noising and Denoising
Amplayo, R. K.; and Lapata, M. 2020 · 1945
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REALM: Retrieval-augmented language model pre-training
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Language Models are Few-Shot Learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T. J.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2005
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Hidden Factors and Hidden Topics: Understanding Rating Dimensions with Review Text
McAuley, J.; and Leskovec, J. 2013 · 2013
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Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
Zhang, Y.; Lai, G.; Zhang, M.; Zhang, Y.; Liu, Y.; and Ma, S. 2014 · 2014
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Wide & Deep Learning for Recommender Systems
Cheng, H.-T.; Koc, L.; Harmsen, J.; Shaked, T.; Chandra, T.; Aradhye, H.; Anderson, G.; Corrado, G.; Chai, W.; Ispir, M.; Anil, R.; Haque, Z.; Hong, L.; Jain, V.; Liu, X.; and Shah, H. 2016 · 2016
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Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering
He, R.; and McAuley, J. 2016 · 2016
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A Diversity-Promoting Objective Function for Neural Conversation Models
Li, J.; Galley, M.; Brockett, C.; Gao, J.; and Dolan, B. 2016 · 2016
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Learning to Generate Product Reviews from Attributes
Dong, L.; Huang, S.; Wei, F.; Lapata, M.; Zhou, M.; and Xu, K. 2017 · 2017
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Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
Hokamp, C.; and Liu, Q. 2017 · 2017
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Neural Rating Regression with Abstractive Tips Generation for Recommendation
Li, P.; Wang, Z.; Ren, Z.; Bing, L.; and Lam, W. 2017 · 2017
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Estimating Reactions and Recommending Products with Generative Models of Reviews
Ni, J.; Lipton, Z. C.; Vikram, S.; and McAuley, J. 2017 · 2017
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Training Classifiers with Natural Language Explanations
Hancock, B.; Varma, P.; Wang, S.; Bringmann, M.; Liang, P.; and Ré, C. 2018 · 2018
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Learning to Generate Move-by-Move Commentary for Chess Games from Large-Scale Social Forum Data
Jhamtani, H.; Gangal, V.; Hovy, E.; Neubig, G.; and Berg-Kirkpatrick, T. 2018 · 2018
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Personalized Review Generation By Expanding Phrases and Attending on Aspect-Aware Representations
Ni, J.; and McAuley, J. 2018 · 2018
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Deep Interest Network for Click-Through Rate Prediction
Zhou, G.; Zhu, X.; Song, C.; Fan, Y.; Zhu, H.; Ma, X.; Yan, Y.; Jin, J.; Li, H.; and Gai, K. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
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Unsupervised Opinion Summarization as Copycat-Review Generation
Bražinskas, A.; Lapata, M.; and Titov, I. 2020 · 2020
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Lewis, P. S. H.; Perez, E.; Piktus, A.; Petroni, F.; Karpukhin, V.; Goyal, N.; Küttler, H.; Lewis, M.; Yih, W.; Rocktäschel, T.; Riedel, S.; and Kiela, D. 2020 · 2020
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Convex Aggregation for Opinion Summarization
Iso, H.; Wang, X.; Suhara, Y.; Angelidis, S.; and Tan, W.-C. 2021 · 2021
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Personalized Transformer for Explainable Recommendation
Li, L.; Zhang, Y.; and Chen, L. 2021 · 2021
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Entity-Based Knowledge Conflicts in Question Answering
Longpre, S.; Perisetla, K.; Chen, A.; Ramesh, N.; DuBois, C.; and Singh, S. 2021 · 2021
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Unsupervised Enrichment of Persona-grounded Dialog with Background Stories
Majumder, B. P.; Berg-Kirkpatrick, T.; McAuley, J.; and Jhamtani, H. 2021 · 2021
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Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
Pagnoni, A.; Balachandran, V.; and Tsvetkov, Y. 2021 · 2021
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MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
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Li, C.; Gao, X.; Li, Y.; Peng, B.; Li, X.; Zhang, Y.; and Gao, J. 2020 · 2020
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Generate Neural Template Explanations for Recommendation
Li, L.; Zhang, Y.; and Chen, L. 2020 · 2020
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Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs
Marasović, A.; Bhagavatula, C.; Park, J. s.; Le Bras, R.; Smith, N. A.; and Choi, Y. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
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MPNet: Masked and Permuted Pre-training for Language Understanding
Song, K.; Tan, X.; Qin, T.; Lu, J.; and Liu, T. 2020 · 2020
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Transformers: State-of-the-Art Natural Language Processing
Wolf, T.; Debut, L.; Sanh, V.; Chaumond, J.; Delangue, C.; Moi, A.; Cistac, P.; Rault, T.; Louf, R.; Funtowicz, M.; Davison, J.; Shleifer, S.; von Platen, P.; Ma, C.; Jernite, Y.; Plu, J.; Xu, C.; Le Scao, T.; Gugger, S.; Drame, M.; Lhoest, Q.; and Rush, A. 2020 · 2020
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Towards Interpretable Natural Language Understanding with Explanations as Latent Variables
Zhou, W.; Hu, J.; Zhang, H.; Liang, X.; Sun, M.; Xiong, C.; and Tang, J. 2020 · 2020
Cited alongside, same era.
Pillutla, K.; Swayamdipta, S.; Zellers, R.; Thickstun, J.; Welleck, S.; Choi, Y.; and Harchaoui, Z. 2021 · 2021
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Few-Shot Question Answering by Pretraining Span Selection
Ram, O.; Kirstain, Y.; Berant, J.; Globerson, A.; and Levy, O. 2021 · 2021
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General-Purpose Question-Answering with Macaw
Tafjord, O.; and Clark, P. 2021 · 2021
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Measuring Association Between Labels and Free-Text Rationales
Wiegreffe, S.; Marasović, A.; and Smith, N. A. 2021 · 2021
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Learning from Perturbations: Diverse and Informative Dialogue Generation with Inverse Adversarial Training
Zhou, W.; Li, Q.; and Li, C. 2021 · 2021
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Improving Personalized Explanation Generation through Visualization
Geng, S.; Fu, Z.; Ge, Y.; Li, L.; de Melo, G.; and Zhang, Y. 2022 · 2022
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Personalized Prompt Learning for Explainable Recommendation
Li, L.; Zhang, Y.; and Chen, L. 2022 · 2022
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Rethinking and Refining the Distinct Metric
Liu, S.; Sabour, S.; Zheng, Y.; Ke, P.; Zhu, X.; and Huang, M. 2022 · 2022
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Rationale-Inspired Natural Language Explanations with Commonsense
Majumder, B. P.; Camburu, O.; Lukasiewicz, T.; and McAuley, J. J. 2022 · 2022
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