{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:31:00Z","timestamp":1772908260519,"version":"3.50.1"},"reference-count":160,"publisher":"Association for Computing Machinery (ACM)","issue":"11s","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Science Foundation","award":["IIS-1849816, CCF-1901059, and IIS-2119531"],"award-info":[{"award-number":["IIS-1849816, CCF-1901059, and IIS-2119531"]}]},{"name":"Agriculture and Food Research Initiative","award":["2020-67021-32799"],"award-info":[{"award-number":["2020-67021-32799"]}]},{"name":"USDA National Institute of Food and Agriculture, U.S.","award":["HR001120C0123, FA8750-18-2-0014, and FA8750-19-2-1004"],"award-info":[{"award-number":["HR001120C0123, FA8750-18-2-0014, and FA8750-19-2-1004"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2022,1,31]]},"abstract":"<jats:p>\n            The goal of text-to-text generation is to make machines express like a human in many applications such as conversation, summarization, and translation. It is one of the most important yet challenging tasks in natural language processing (NLP). Various neural encoder-decoder models have been proposed to achieve the goal by learning to map input text to output text. However, the input text alone often provides limited knowledge to generate the desired output, so the performance of text generation is still far from satisfaction in many real-world scenarios. To address this issue, researchers have considered incorporating (i) internal knowledge embedded in the input text and (ii) external knowledge from outside sources such as knowledge base and knowledge graph into the text generation system. This research topic is known as\n            <jats:italic>knowledge-enhanced text generation<\/jats:italic>\n            . In this survey, we present a comprehensive review of the research on this topic over the past five years. The main content includes two parts: (i) general methods and architectures for integrating knowledge into text generation; (ii) specific techniques and applications according to different forms of knowledge data. This survey can have broad audiences, researchers and practitioners, in academia and industry.\n          <\/jats:p>","DOI":"10.1145\/3512467","type":"journal-article","created":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T13:06:20Z","timestamp":1648213580000},"page":"1-38","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":160,"title":["A Survey of Knowledge-enhanced Text Generation"],"prefix":"10.1145","volume":"54","author":[{"given":"Wenhao","family":"Yu","sequence":"first","affiliation":[{"name":"University of Notre Dame, IN, USA"}]},{"given":"Chenguang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA, USA"}]},{"given":"Zaitang","family":"Li","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, China"}]},{"given":"Zhiting","family":"Hu","sequence":"additional","affiliation":[{"name":"University of California at San Diego, San Diego, CA, USA"}]},{"given":"Qingyun","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}]},{"given":"Heng","family":"Ji","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}]},{"given":"Meng","family":"Jiang","sequence":"additional","affiliation":[{"name":"University of Notre Dame, IN, USA"}]}],"member":"320","published-online":{"date-parts":[[2022,11,10]]},"reference":[{"key":"e_1_3_2_2_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Aharoni Roee","year":"2017","unstructured":"Roee Aharoni and Yoav Goldberg. 2017. Towards string-to-tree neural machine translation. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i14.17482"},{"key":"e_1_3_2_4_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Bahdanau Dzmitry","year":"2015","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1209"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1454"},{"key":"e_1_3_2_7_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Beck Daniel","year":"2018","unstructured":"Daniel Beck, Gholamreza Haffari, and Trevor Cohn. 2018. Graph-to-sequence learning using gated graph neural networks. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_8_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Bhagavatula Chandra","year":"2020","unstructured":"Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, and Yejin Choi. 2020. Abductive commonsense reasoning. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6238"},{"key":"e_1_3_2_10_2","volume-title":"J. Mach. Learn. Res","author":"Blei David M.","year":"2003","unstructured":"David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet allocation. J. Mach. Learn. Res."},{"key":"e_1_3_2_11_2","volume-title":"Conference on Advances in Neural Information Processing Systems (NeurIPS)","author":"Bordes Antoine","year":"2013","unstructured":"Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Conference on Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9499"},{"key":"e_1_3_2_13_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Cao Ziqiang","year":"2018","unstructured":"Ziqiang Cao, Wenjie Li, Sujian Li, and Furu Wei. 2018. Retrieve, rerank and rewrite: Soft template based neural summarization. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_14_2","volume-title":"Annual Meeting of the Association of Computational Linguistics (ACL)","author":"Chang Ming-Wei","year":"2007","unstructured":"Ming-Wei Chang, Lev Ratinov, and Dan Roth. 2007. Guiding semi-supervision with constraint-driven learning. In Annual Meeting of the Association of Computational Linguistics (ACL)."},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11910"},{"key":"e_1_3_2_16_2","volume-title":"Exp. Syst. Applic","author":"Chen Xiaojun","year":"2020","unstructured":"Xiaojun Chen, Shengbin Jia, and Yang Xiang. 2020. A review: Knowledge reasoning over knowledge graph. Exp. Syst. Applic."},{"key":"e_1_3_2_17_2","volume-title":"International Conference of Learning Representation (ICLR).","author":"Chen Yu","year":"2020","unstructured":"Yu Chen, Lingfei Wu, and Mohammed J. Zaki. 2020. Reinforcement learning based graph-to-sequence model for natural question generation. In International Conference of Learning Representation (ICLR)."},{"key":"e_1_3_2_18_2","volume-title":"Synthesis Lectures on Artificial Intelligence and Machine Learning","author":"Chen Zhiyuan","year":"2018","unstructured":"Zhiyuan Chen and Bing Liu. 2018. Lifelong machine learning. In Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers."},{"key":"e_1_3_2_19_2","volume-title":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Cheng Liying","year":"2020","unstructured":"Liying Cheng, Dekun Wu, Lidong Bing, Yan Zhang, Zhanming Jie, Wei Lu, and Luo Si. 2020. ENTDESC: Entity description generation by exploring knowledge graph. In Conference on Empirical Methods in Natural Language Processing (EMNLP)."},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1308"},{"key":"e_1_3_2_21_2","volume-title":"arXiv preprint arXiv:1708.00897","author":"Choudhary Sajal","year":"2017","unstructured":"Sajal Choudhary, Prerna Srivastava, Lyle Ungar, and Joao Sedoc. 2017. Domain aware neural dialog system. arXiv preprint arXiv:1708.00897."},{"key":"e_1_3_2_22_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Dathathri Sumanth","year":"2020","unstructured":"Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2020. Plug and play language models: A simple approach to controlled text generation. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_23_2","volume-title":"Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)."},{"key":"e_1_3_2_24_2","volume-title":"International Conference on Learning Representations (ICLR)","author":"Diederik P. Kingma","year":"2014","unstructured":"P. Kingma Diederik, Max Welling, et\u00a0al. 2014. Auto-encoding variational Bayes. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_25_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Dinan Emily","year":"2019","unstructured":"Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019. Wizard of Wikipedia: Knowledge-powered conversational agents. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.56"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/E17-2075"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1428"},{"key":"e_1_3_2_29_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Fan Angela","year":"2019","unstructured":"Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019. ELI5: Long form question answering. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.182"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6277"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1017"},{"key":"e_1_3_2_33_2","volume-title":"J. Mach. Learn. Res","author":"Ganchev Kuzman","year":"2010","unstructured":"Kuzman Ganchev, Jennifer Gillenwater, Ben Taskar, et\u00a0al. 2010. Posterior regularization for structured latent variable models. J. Mach. Learn. Res."},{"key":"e_1_3_2_34_2","volume-title":"Neurocomputing","author":"Gao Ce","year":"2019","unstructured":"Ce Gao and Jiangtao Ren. 2019. A topic-driven model for learning to generate diverse sentences. Neurocomputing."},{"key":"e_1_3_2_35_2","volume-title":"arXiv preprint arXiv:2007.15780","author":"Garbacea Cristina","year":"2020","unstructured":"Cristina Garbacea and Qiaozhu Mei. 2020. Neural language generation: Formulation, methods, and evaluation. arXiv preprint arXiv:2007.15780."},{"key":"e_1_3_2_36_2","volume-title":"J. Artif. Intell. Res","author":"Gatt Albert","year":"2018","unstructured":"Albert Gatt and Emiel Krahmer. 2018. Survey of the state of the art in natural language generation: Core tasks, applications and evaluation. J. Artif. Intell. Res."},{"key":"e_1_3_2_37_2","volume-title":"International Conference on Machine Learning (ICML)","author":"Gehring Jonas","year":"2017","unstructured":"Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N. Dauphin. 2017. Convolutional sequence to sequence learning. In International Conference on Machine Learning (ICML)."},{"key":"e_1_3_2_38_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Gehrmann Sebastian","year":"2021","unstructured":"Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna Clinciu, Dipanjan Das, Kaustubh D. Dhole, et\u00a0al. 2021. The GEM benchmark: Natural language generation, its evaluation and metrics. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1443"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11977"},{"key":"e_1_3_2_41_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Gu Jiatao","year":"2016","unstructured":"Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O. K. Li. 2016. Incorporating copying mechanism in sequence-to-sequence learning. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12013"},{"key":"e_1_3_2_43_2","volume-title":"Trans. Assoc. Computat. Ling","author":"Guan Jian","year":"2020","unstructured":"Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, and Minlie Huang. 2020. A knowledge-enhanced pretraining model for commonsense story generation. Trans. Assoc. Computat. Ling."},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33016473"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525295"},{"key":"e_1_3_2_46_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"He Shizhu","year":"2017","unstructured":"Shizhu He, Cao Liu, Kang Liu, and Jun Zhao. 2017. Generating natural answers by incorporating copying and retrieving mechanisms in sequence-to-sequence learning. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_47_2","volume-title":"ACM Comput. Surv","author":"Hossain MD Zakir","year":"2019","unstructured":"MD Zakir Hossain, Ferdous Sohel, Mohd Fairuz Shiratuddin, and Hamid Laga. 2019. A comprehensive survey of deep learning for image captioning. ACM Comput. Surv."},{"key":"e_1_3_2_48_2","volume-title":"International Conference on Machine Learning (ICML)","author":"Hu Zhiting","year":"2017","unstructured":"Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P. Xing. 2017. Toward controlled generation of text. In International Conference on Machine Learning (ICML)."},{"key":"e_1_3_2_49_2","volume-title":"Conference on Advances in Neural Information Processing Systems","author":"Hu Zhiting","year":"2018","unstructured":"Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, and Eric Xing. 2018. Deep generative models with learnable knowledge constraints. In Conference on Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_50_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Hua Xinyu","year":"2019","unstructured":"Xinyu Hua, Zhe Hu, and Lu Wang. 2019. Argument generation with retrieval, planning, and realization. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_51_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Hua Xinyu","year":"2018","unstructured":"Xinyu Hua and Lu Wang. 2018. Neural argument generation augmented with externally retrieved evidence. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_52_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Huang Luyang","year":"2020","unstructured":"Luyang Huang, Lingfei Wu, and Lu Wang. 2020. Knowledge graph-augmented abstractive summarization with semantic-driven cloze reward. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_53_2","volume-title":"J. King Saud Univ.-Comput. Inf. Sci","author":"Iqbal Touseef","year":"2020","unstructured":"Touseef Iqbal and Shaima Qureshi. 2020. The survey: Text generation models in deep learning. In J. King Saud Univ.-Comput. Inf. Sci. Elsevier."},{"key":"e_1_3_2_54_2","volume-title":"Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and International Joint Conference on Natural Language (AACL-IJCNLP)","author":"Ji Haozhe","year":"2020","unstructured":"Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, and Minlie Huang. 2020. Generating commonsense explanation by extracting bridge concepts from reasoning paths. In Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and International Joint Conference on Natural Language (AACL-IJCNLP)."},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.54"},{"key":"e_1_3_2_56_2","volume-title":"arXiv preprint arXiv:2002.00388","author":"Ji Shaoxiong","year":"2020","unstructured":"Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and Philip S. Yu. 2020. A survey on knowledge graphs: Representation, acquisition and applications. arXiv preprint arXiv:2002.00388."},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6312"},{"key":"e_1_3_2_58_2","volume-title":"arXiv preprint arXiv:2101.06561","author":"Khashabi Daniel","year":"2021","unstructured":"Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, and Daniel S. Weld. 2021. Genie: A leaderboard for human-in-the-loop evaluation of text generation. arXiv preprint arXiv:2101.06561."},{"key":"e_1_3_2_59_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Kim Byeongchang","year":"2020","unstructured":"Byeongchang Kim, Jaewoo Ahn, and Gunhee Kim. 2020. Sequential latent knowledge selection for knowledge-grounded dialogue. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.207"},{"key":"e_1_3_2_61_2","volume-title":"Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)","author":"Koncel-Kedziorski Rik","year":"2019","unstructured":"Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, and Hannaneh Hajishirzi. 2019. Text generation from knowledge graphs with graph transformers. In Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)."},{"key":"e_1_3_2_62_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.393"},{"key":"e_1_3_2_63_2","doi-asserted-by":"publisher","DOI":"10.5555\/2145432.2145494"},{"key":"e_1_3_2_64_2","volume-title":"Nature","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. In Nature. Nature Publishing Group."},{"key":"e_1_3_2_65_2","volume-title":"Conference on Advances in Neural Information Processing Systems (NeurIPS)","author":"Lewis Patrick","year":"2020","unstructured":"Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich K\u00fcttler, Mike Lewis, Wen-tau Yih, Tim Rockt\u00e4schel, et\u00a0al. 2020. Retrieval-augmented generation for knowledge-intensive NLP tasks. In Conference on Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2009"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6333"},{"key":"e_1_3_2_68_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1071"},{"key":"e_1_3_2_69_2","volume-title":"Annual Meeting of Association for Computational Linguistics (ACL)","author":"Li Wei","year":"2021","unstructured":"Wei Li, Xinyan Xiao, Jiachen Liu, Hua Wu, Haifeng Wang, and Junping Du. 2021. Leveraging graph to improve abstractive multi-document summarization. In Annual Meeting of Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_70_2","volume-title":"Annual Meeting of Association Computational Linguistics (ACL)","author":"Li Wei","year":"2019","unstructured":"Wei Li, Jingjing Xu, Yancheng He, ShengLi Yan, Yunfang Wu, and Xu Sun. 2019. Coherent comments generation for Chinese articles with a graph-to-sequence model. In Annual Meeting of Association Computational Linguistics (ACL)."},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/706"},{"key":"e_1_3_2_72_2","volume-title":"International Conference on Computational Linguistics (COLING)","author":"Liao Kexin","year":"2018","unstructured":"Kexin Liao, Logan Lebanoff, and Fei Liu. 2018. Abstract meaning representation for multi-document summarization. In International Conference on Computational Linguistics (COLING)."},{"key":"e_1_3_2_73_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.165"},{"key":"e_1_3_2_74_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Liu Dayiheng","year":"2021","unstructured":"Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Weizhu Chen, Jie Fu, Linjun Shou, Ming Gong, et\u00a0al. 2021. GLGE: A new general language generation evaluation benchmark. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_75_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i03.5681"},{"key":"e_1_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358102"},{"key":"e_1_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i7.16796"},{"key":"e_1_3_2_78_2","volume-title":"Conference on Empirical Methods in Natural Language Processing and International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","author":"Liu Zhibin","year":"2019","unstructured":"Zhibin Liu, Zheng-Yu Niu, Hua Wu, and Haifeng Wang. 2019. Knowledge aware conversation generation with reasoning on augmented graph. In Conference on Empirical Methods in Natural Language Processing and International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)."},{"key":"e_1_3_2_79_2","volume-title":"Annual Meeting of Association for Computational Linguistics (ACL)","author":"Madotto Andrea","year":"2018","unstructured":"Andrea Madotto, Chien-Sheng Wu, and Pascale Fung. 2018. Mem2Seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems. In Annual Meeting of Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_80_2","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273571"},{"key":"e_1_3_2_81_2","volume-title":"Annual Meeting of the Association for Computational Linguistics: System Demonstration (ACL)","author":"Manning Christopher D.","year":"2014","unstructured":"Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Rose Finkel, Steven Bethard, and David McClosky. 2014. The stanford CoreNLP natural language processing toolkit. In Annual Meeting of the Association for Computational Linguistics: System Demonstration (ACL)."},{"key":"e_1_3_2_82_2","article-title":"The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision","author":"Mao Jiayuan","year":"2019","unstructured":"Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, and Jiajun Wu. 2019. The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision. In International Conference for Learning Representation (ICLR).","journal-title":"International Conference for Learning Representation (ICLR)"},{"key":"e_1_3_2_83_2","volume-title":"arXiv preprint arXiv:1802.06024","author":"Mazumder Sahisnu","year":"2018","unstructured":"Sahisnu Mazumder, Nianzu Ma, and Bing Liu. 2018. Towards a continuous knowledge learning engine for chatbots. arXiv preprint arXiv:1802.06024."},{"key":"e_1_3_2_84_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6370"},{"key":"e_1_3_2_85_2","volume-title":"Manag. Sci","author":"Menon Tanya","year":"2003","unstructured":"Tanya Menon and Jeffrey Pfeffer. 2003. Valuing internal vs. external knowledge: Explaining the preference for outsiders. Manag. Sci."},{"key":"e_1_3_2_86_2","volume-title":"International Conference on Machine Learning (ICML)","author":"Miao Yishu","year":"2017","unstructured":"Yishu Miao, Edward Grefenstette, and Phil Blunsom. 2017. Discovering discrete latent topics with neural variational inference. In International Conference on Machine Learning (ICML)."},{"key":"e_1_3_2_87_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1255"},{"key":"e_1_3_2_88_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Moon Seungwhan","year":"2019","unstructured":"Seungwhan Moon, Pararth Shah, Anuj Kumar, and Rajen Subba. 2019. OpenDialKG: Explainable conversational reasoning with attention-based walks over knowledge graphs. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_89_2","volume-title":"Conference on Computational Linguistics: Technical Papers (COLING)","author":"Mou Lili","year":"2016","unstructured":"Lili Mou, Yiping Song, Rui Yan, Ge Li, Lu Zhang, and Zhi Jin. 2016. Sequence to backward and forward sequences: A content-introducing approach to generative short-text conversation. In Conference on Computational Linguistics: Technical Papers (COLING)."},{"key":"e_1_3_2_90_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30793-6_29"},{"key":"e_1_3_2_91_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K16-1028"},{"key":"e_1_3_2_92_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1206"},{"key":"e_1_3_2_93_2","volume-title":"International Conference on Computational Linguistics (COLING)","author":"Niklaus Christina","year":"2018","unstructured":"Christina Niklaus, Matthias Cetto, Andr\u00e9 Freitas, and Siegfried Handschuh. 2018. A survey on open information extraction. In International Conference on Computational Linguistics (COLING)."},{"key":"e_1_3_2_94_2","volume-title":"Trans. Assoc. Computat. Ling","author":"Niu Tong","year":"2018","unstructured":"Tong Niu and Mohit Bansal. 2018. Polite dialogue generation without parallel data. Trans. Assoc. Computat. Ling."},{"key":"e_1_3_2_95_2","volume-title":"Conference on Empirical Methods in Natural Language Processing and International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","author":"Niu Zheng-Yu","year":"2019","unstructured":"Zheng-Yu Niu, Hua Wu, Haifeng Wang, et\u00a0al. 2019. Knowledge aware conversation generation with explainable reasoning over augmented graphs. In Conference on Empirical Methods in Natural Language Processing and International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)."},{"key":"e_1_3_2_96_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Pan Liangming","year":"2020","unstructured":"Liangming Pan, Yuxi Xie, Yansong Feng, Tat-Seng Chua, and Min-Yen Kan. 2020. Semantic graphs for generating deep questions. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_97_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.200"},{"key":"e_1_3_2_98_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1250"},{"key":"e_1_3_2_99_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Qin Lianhui","year":"2019","unstructured":"Lianhui Qin, Michel Galley, Chris Brockett, Xiaodong Liu, Xiang Gao, Bill Dolan, Yejin Choi, and Jianfeng Gao. 2019. Conversing by reading: Contentful neural conversation with on-demand machine reading. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_100_2","volume-title":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Qin Lianhui","year":"2020","unstructured":"Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena Hwang, Ronan Le Bras, Antoine Bosselut, and Yejin Choi. 2020. Backpropagation-based decoding for unsupervised counterfactual and abductive reasoning. In Conference on Empirical Methods in Natural Language Processing (EMNLP)."},{"key":"e_1_3_2_101_2","volume-title":"J. Mach. Learn. Res","author":"Raffel Colin","year":"2020","unstructured":"Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res."},{"key":"e_1_3_2_102_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1264"},{"key":"e_1_3_2_103_2","volume-title":"North American Chapter of the Association for Computational Linguistics (NAACL)","author":"Reddy Revanth Gangi","year":"2019","unstructured":"Revanth Gangi Reddy, Danish Contractor, Dinesh Raghu, and Sachindra Joshi. 2019. Multi-Level memory for task oriented dialogs. In North American Chapter of the Association for Computational Linguistics (NAACL)."},{"key":"e_1_3_2_104_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6395"},{"key":"e_1_3_2_105_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_106_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"See Abigail","year":"2017","unstructured":"Abigail See, Peter J. Liu, and Christopher D. Manning. 2017. Get to the point: Summarization with pointer-generator networks. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_107_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W16-2209"},{"key":"e_1_3_2_108_2","volume-title":"Int. J. Comput. Applic","author":"Siddiqi Sifatullah","year":"2015","unstructured":"Sifatullah Siddiqi and Aditi Sharan. 2015. Keyword and keyphrase extraction techniques: A literature review. Int. J. Comput. Applic. Foundation of Computer Science."},{"key":"e_1_3_2_109_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/721"},{"key":"e_1_3_2_110_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Song Zhenqiao","year":"2019","unstructured":"Zhenqiao Song, Xiaoqing Zheng, Lu Liu, Mu Xu, and Xuan-Jing Huang. 2019. Generating responses with a specific emotion in dialog. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_111_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11164"},{"key":"e_1_3_2_112_2","volume-title":"Conference on Advances in Neural Information Processing Systems (NeurIPS)","author":"Sukhbaatar Sainbayar","year":"2015","unstructured":"Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et\u00a0al. 2015. End-to-end memory networks. In Conference on Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_113_2","volume-title":"Conference on Advances in Neural Information Processing Systems (NeurIPS)","author":"Sutskever Ilya","year":"2014","unstructured":"Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014. Sequence to sequence learning with neural networks. In Conference on Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_114_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.510"},{"key":"e_1_3_2_115_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Tang Jianheng","year":"2019","unstructured":"Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric Xing, and Zhiting Hu. 2019. Target-guided open-domain conversation. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_116_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.61"},{"key":"e_1_3_2_117_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1194"},{"key":"e_1_3_2_118_2","volume-title":"Conference on Advances in Neural Information Processing Systems (NeurIPS)","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Conference on Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_119_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Veli\u010dkovi\u0107 Petar","year":"2018","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2018. Graph attention networks. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_120_2","volume-title":"14th Workshop on Semantic Evaluation","author":"Wang Cunxiang","year":"2020","unstructured":"Cunxiang Wang, Shuailong Liang, Yili Jin, Yilong Wang, Xiaodan Zhu, and Yue Zhang. 2020. SemEval-2020 task 4: Commonsense validation and explanation. In 14th Workshop on Semantic Evaluation."},{"key":"e_1_3_2_121_2","volume-title":"arXiv preprint arXiv:2003.00814","author":"Wang Hao","year":"2020","unstructured":"Hao Wang, Bin Guo, Wei Wu, and Zhiwen Yu. 2020. Towards information-rich, logical text generation with knowledge-enhanced neural models. arXiv preprint arXiv:2003.00814."},{"key":"e_1_3_2_122_2","volume-title":"Annual Meeting of Association for Computational Linguistics (ACL)","author":"Wang Han","year":"2021","unstructured":"Han Wang, Yang Liu, Chenguang Zhu, Linjun Shou, Ming Gong Gong, Yichong Xu, and Michael Zeng. 2021. Retrieval enhanced model for commonsense generation. In Annual Meeting of Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_123_2","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330836"},{"key":"e_1_3_2_124_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6453"},{"key":"e_1_3_2_125_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Wang Kai","year":"2019","unstructured":"Kai Wang, Xiaojun Quan, and Rui Wang. 2019. BiSET: Bi-directional selective encoding with template for abstractive summarization. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_126_2","volume-title":"Annual Meeting of Association Computational Linguistics (ACL)","author":"Wang Qingyun","year":"2019","unstructured":"Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, and Yi Luan. 2019. PaperRobot: Incremental draft generation of scientific ideas. In Annual Meeting of Association Computational Linguistics (ACL)."},{"key":"e_1_3_2_127_2","volume-title":"IEEE Trans. Knowl. Data Eng","author":"Wang Quan","year":"2017","unstructured":"Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 2017. Knowledge graph embedding: A survey of approaches and applications. IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_2_128_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1015"},{"key":"e_1_3_2_129_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.194"},{"key":"e_1_3_2_130_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017257"},{"key":"e_1_3_2_131_2","volume-title":"International Conference for Learning Representation (ICLR)","author":"Wu Chien-Sheng","year":"2019","unstructured":"Chien-Sheng Wu, Richard Socher, and Caiming Xiong. 2019. Global-to-local memory pointer networks for task-oriented dialogue. In International Conference for Learning Representation (ICLR)."},{"key":"e_1_3_2_132_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Wu Sixing","year":"2020","unstructured":"Sixing Wu, Ying Li, Dawei Zhang, Yang Zhou, and Zhonghai Wu. 2020. Diverse and informative dialogue generation with context-specific commonsense knowledge awareness. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_133_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/521"},{"key":"e_1_3_2_134_2","volume-title":"IEEE Trans. Neural Netw. Learn. Syst","author":"Wu Zonghan","year":"2020","unstructured":"Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and Philip S. Yu. 2020. A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst."},{"key":"e_1_3_2_135_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10981"},{"key":"e_1_3_2_136_2","volume-title":"International Conference of Learning Representation (ICLR)","author":"Xiong Wenhan","year":"2020","unstructured":"Wenhan Xiong, Jingfei Du, William Yang Wang, and Veselin Stoyanov. 2020. Pretrained encyclopedia: Weakly supervised knowledge-pretrained language model. In International Conference of Learning Representation (ICLR)."},{"key":"e_1_3_2_137_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1060"},{"key":"e_1_3_2_138_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Xu Jun","year":"2020","unstructured":"Jun Xu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, and Ting Liu. 2020. Conversational graph grounded policy learning for open-domain conversation generation. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_139_2","volume-title":"European Conference on Artificial Intelligence (ECAI)","author":"Xu Minghong","year":"2020","unstructured":"Minghong Xu, Piji Li, Haoran Yang, Pengjie Ren, Zhaochun Ren, Zhumin Chen, and Jun Ma. 2020. A neural topical expansion framework for unstructured persona-oriented dialogue generation. In European Conference on Artificial Intelligence (ECAI)."},{"key":"e_1_3_2_140_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Yang Pengcheng","year":"2019","unstructured":"Pengcheng Yang, Lei Li, Fuli Luo, Tianyu Liu, and Xu Sun. 2019. Enhancing topic-to-essay generation with external commonsense knowledge. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_141_2","article-title":"KG-FiD: Infusing knowledge graph in fusion-in-decoder for open-domain question answering","author":"Yu Donghan","year":"2022","unstructured":"Donghan Yu, Chenguang Zhu, Yuwei Fang, Wenhao Yu, Shuohang Wang, Yichong Xu, Xiang Ren, Yiming Yang, and Michael Zeng. 2022. KG-FiD: Infusing knowledge graph in fusion-in-decoder for open-domain question answering. In Annual Meeting of the Association for Computational Linguistics (ACL).","journal-title":"Annual Meeting of the Association for Computational Linguistics (ACL)"},{"key":"e_1_3_2_142_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21417"},{"key":"e_1_3_2_143_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380175"},{"key":"e_1_3_2_144_2","article-title":"Dict-BERT: Enhancing language model pre-training with dictionary","author":"Yu Wenhao","year":"2021","unstructured":"Wenhao Yu, Chenguang Zhu, Yuwei Fang, Donghan Yu, Shuohang Wang, Yichong Xu, Michael Zeng, and Meng Jiang. 2021. Dict-BERT: Enhancing language model pre-training with dictionary. arXiv preprint arXiv:2110.06490.","journal-title":"arXiv preprint arXiv:2110.06490"},{"key":"e_1_3_2_145_2","article-title":"Sentence-permuted paragraph generation","author":"Yu Wenhao","year":"2021","unstructured":"Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, and Meng Jiang. 2021. Sentence-permuted paragraph generation. In Conference on Empirical Methods in Natural Language Processing (EMNLP).","journal-title":"Conference on Empirical Methods in Natural Language Processing (EMNLP)"},{"key":"e_1_3_2_146_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467308"},{"key":"e_1_3_2_147_2","volume-title":"Annual Meeting of the Association for Computational Linguistics","author":"Zhang Houyu","year":"2020","unstructured":"Houyu Zhang, Zhenghao Liu, Chenyan Xiong, and Zhiyuan Liu. 2020. Grounded conversation generation as guided traverses in commonsense knowledge graphs. In Annual Meeting of the Association for Computational Linguistics."},{"key":"e_1_3_2_148_2","volume-title":"International Conference on Computational Linguistics: Technical Papers (COLING)","author":"Zhang Jian","year":"2016","unstructured":"Jian Zhang, Liangyou Li, Andy Way, and Qun Liu. 2016. Topic-informed neural machine translation. In International Conference on Computational Linguistics: Technical Papers (COLING)."},{"key":"e_1_3_2_149_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Zhang Jiacheng","year":"2017","unstructured":"Jiacheng Zhang, Yang Liu, Huanbo Luan, Jingfang Xu, and Maosong Sun. 2017. Prior knowledge integration for neural machine translation using posterior regularization. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_150_2","volume-title":"Annual Meeting of Association Computational Linguistics (ACL)","author":"Zhang Saizheng","year":"2018","unstructured":"Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018. Personalizing dialogue agents: I have a dog, do you have pets? In Annual Meeting of Association Computational Linguistics (ACL)."},{"key":"e_1_3_2_151_2","volume-title":"Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Zhang Zhengyan","year":"2019","unstructured":"Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019. ERNIE: Enhanced language representation with informative entities. In Annual Meeting of the Association for Computational Linguistics (ACL)."},{"key":"e_1_3_2_152_2","volume-title":"arXiv preprint arXiv:2009.13282","author":"Zhao Liang","year":"2020","unstructured":"Liang Zhao, Jingjing Xu, Junyang Lin, Yichang Zhang, Hongxia Yang, and Xu Sun. 2020. Graph-based multi-hop reasoning for long text generation. arXiv preprint arXiv:2009.13282."},{"key":"e_1_3_2_153_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-2122-1"},{"key":"e_1_3_2_154_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/643"},{"key":"e_1_3_2_155_2","volume-title":"Conference on Natural Language Processing and Chinese Computing (NLPCC)","author":"Zhou Qingyu","year":"2017","unstructured":"Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, and Ming Zhou. 2017. Neural question generation from text: A preliminary study. In Conference on Natural Language Processing and Chinese Computing (NLPCC)."},{"key":"e_1_3_2_156_2","article-title":"Pre-training text-to-text transformers for concept-centric common sense","author":"Zhou Wangchunshu","year":"2021","unstructured":"Wangchunshu Zhou, Dong-Ho Lee, Ravi Kiran Selvam, Seyeon Lee, Bill Yuchen Lin, and Xiang Ren. 2021. Pre-training text-to-text transformers for concept-centric common sense. In International Conference for Learning Representation.","journal-title":"International Conference for Learning Representation"},{"key":"e_1_3_2_157_2","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00036"},{"key":"e_1_3_2_158_2","volume-title":"Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)","author":"Zhu Chenguang","year":"2021","unstructured":"Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, and Meng Jiang. 2021. Boosting factual correctness of abstractive summarization with knowledge graph. In Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)."},{"key":"e_1_3_2_159_2","volume-title":"J. Mach. Learn. Res","author":"Zhu Jun","year":"2014","unstructured":"Jun Zhu, Ning Chen, and Eric P. Xing. 2014. Bayesian inference with posterior regularization and applications to infinite latent SVMs. J. Mach. Learn. Res."},{"key":"e_1_3_2_160_2","volume-title":"CoRR, abs\/1709.04264","author":"Zhu Wenya","year":"2017","unstructured":"Wenya Zhu, Kaixiang Mo, Yu Zhang, Zhangbin Zhu, Xuezheng Peng, and Qiang Yang. 2017. Flexible end-to-end dialogue system for knowledge grounded conversation. CoRR, abs\/1709.04264."},{"key":"e_1_3_2_161_2","volume-title":"J. Roy. Statist. Societ","author":"Zou Hui","year":"2005","unstructured":"Hui Zou and Trevor Hastie. 2005. Regularization and variable selection via the elastic net. J. Roy. Statist. Societ. Wiley Online Library."}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512467","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3512467","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:11:43Z","timestamp":1750191103000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512467"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,31]]},"references-count":160,"journal-issue":{"issue":"11s","published-print":{"date-parts":[[2022,1,31]]}},"alternative-id":["10.1145\/3512467"],"URL":"https:\/\/doi.org\/10.1145\/3512467","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,31]]},"assertion":[{"value":"2020-10-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-01-10","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-11-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}