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In AAAI. 98--105."},{"key":"e_1_3_2_2_32_1","volume-title":"Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, and Lawrence Carin.","author":"Shen Dinghan","year":"2018","unstructured":"Dinghan Shen , Guoyin Wang , Wenlin Wang , Martin Renqiang Min , Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, and Lawrence Carin. 2018 . Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms. arXiv preprint arXiv:1805.09843 (2018). Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, and Lawrence Carin. 2018. Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms. arXiv preprint arXiv:1805.09843 (2018)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Konstantinos Skianis Fran\u00e7ois Rousseau and Michalis Vazirgiannis. 2016. Regularizing text categorization with clusters of words. In EMNLP. 1827--1837.  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