| Year | Conf. | Topic | Cited | Paper | Authors | Url |
|---|---|---|---|---|---|---|
| 2019 | ACL | # optim-adam, init-glorot, reg-dropout, reg-decay, train-mtl, arch-lstm, arch-bilstm, arch-att, task-condlm, task-seq2seq | 1 | Storyboarding of Recipes: Grounded Contextual Generation | Khyathi Chandu, Eric Nyberg, Alan W Black | https://www.aclweb.org/anthology/P19-1606.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, norm-batch, norm-gradient, train-mtl, activ-relu, arch-rnn, arch-lstm, arch-bilstm, arch-cnn, arch-att, arch-coverage, arch-transformer, pre-fasttext, task-textclass, task-lm | 1 | #YouToo? Detection of Personal Recollections of Sexual Harassment on Social Media | Arijit Ghosh Chowdhury, Ramit Sawhney, Rajiv Ratn Shah, Debanjan Mahata | https://www.aclweb.org/anthology/P19-1241.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, norm-layer, train-augment, arch-gnn, arch-att, arch-selfatt, arch-copy, arch-transformer, search-greedy, pre-glove, pre-bert, task-textclass, task-lm, task-seq2seq, task-tree, task-graph | 2 | Generating Logical Forms from Graph Representations of Text and Entities | Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun | https://www.aclweb.org/anthology/P19-1010.pdf |
| 2019 | ACL | # optim-adam, init-glorot, reg-decay, arch-gnn, arch-att, arch-selfatt, arch-memo, arch-coverage, pre-bert, task-spanlab, task-lm | 7 | Cognitive Graph for Multi-Hop Reading Comprehension at Scale | Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, Jie Tang | https://www.aclweb.org/anthology/P19-1259.pdf |
| 2019 | ACL | # optim-adam, init-glorot, reg-decay, train-augment, arch-rnn, arch-att, arch-bilinear, arch-subword, task-textclass, task-lm, task-seq2seq, task-relation | 5 | Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology | Ran Zmigrod, Sebastian J. Mielke, Hanna Wallach, Ryan Cotterell | https://www.aclweb.org/anthology/P19-1161.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, pool-max, arch-rnn, arch-cnn, arch-coverage, search-beam, pre-glove, pre-skipthought, task-textpair, task-lm | 0 | A Cross-Domain Transferable Neural Coherence Model | Peng Xu, Hamidreza Saghir, Jin Sung Kang, Teng Long, Avishek Joey Bose, Yanshuai Cao, Jackie Chi Kit Cheung | https://www.aclweb.org/anthology/P19-1067.pdf |
| 2019 | ACL | # optim-adam, reg-decay, arch-lstm, arch-att, arch-coverage, comb-ensemble, pre-paravec, latent-topic, task-relation | 0 | Modeling Financial Analysts’ Decision Making via the Pragmatics and Semantics of Earnings Calls | Katherine Keith, Amanda Stent | https://www.aclweb.org/anthology/P19-1047.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, train-transfer, arch-rnn, arch-lstm, arch-cnn, arch-att, arch-memo, comb-ensemble, task-textclass, task-lm, task-seq2seq | 0 | StRE: Self Attentive Edit Quality Prediction in Wikipedia | Soumya Sarkar, Bhanu Prakash Reddy, Sandipan Sikdar, Animesh Mukherjee | https://www.aclweb.org/anthology/P19-1387.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, reg-labelsmooth, train-mll, train-transfer, arch-att, arch-selfatt, arch-transformer, comb-ensemble, search-beam, pre-elmo, pre-bert, task-textclass, task-textpair, task-lm, task-seq2seq, task-cloze | 1 | A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning | Gonçalo M. Correia, André F. T. Martins | https://www.aclweb.org/anthology/P19-1292.pdf |
| 2019 | ACL | # optim-adam, reg-stopping, reg-patience, reg-decay, arch-att, arch-coverage, arch-transformer, comb-ensemble, pre-elmo, pre-bert, task-textpair, task-lm | 1 | GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification | Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, Maosong Sun | https://www.aclweb.org/anthology/P19-1085.pdf |
| 2019 | ACL | # optim-adagrad, reg-decay, train-transfer, arch-lstm, arch-bilstm, arch-att, arch-selfatt, pre-glove, adv-train, task-textpair, task-seqlab | 5 | OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs | Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba | https://www.aclweb.org/anthology/P19-1081.pdf |
| 2019 | ACL | # optim-adam, reg-dropout, reg-decay, train-mtl, arch-rnn, arch-lstm, arch-bilstm, arch-gru, arch-bigru, arch-cnn, arch-att, pre-fasttext, pre-glove, struct-crf, task-textclass, task-seqlab, task-lm, task-seq2seq, task-relation, task-alignment | 1 | Exploring Sequence-to-Sequence Learning in Aspect Term Extraction | Dehong Ma, Sujian Li, Fangzhao Wu, Xing Xie, Houfeng Wang | https://www.aclweb.org/anthology/P19-1344.pdf |
| 2019 | ACL | # reg-decay, arch-lstm, arch-att, arch-selfatt, comb-ensemble, pre-glove, pre-elmo, pre-bert, task-textclass, task-textpair, task-lm, task-seq2seq, task-tree | 8 | Explain Yourself! Leveraging Language Models for Commonsense Reasoning | Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, Richard Socher | https://www.aclweb.org/anthology/P19-1487.pdf |
| 2019 | ACL | # optim-sgd, reg-dropout, reg-worddropout, reg-norm, reg-decay, train-mtl, arch-rnn, arch-lstm, arch-transformer, task-lm, task-seq2seq | 2 | Improved Language Modeling by Decoding the Past | Siddhartha Brahma | https://www.aclweb.org/anthology/P19-1142.pdf |
| 2019 | EMNLP | # optim-adam, optim-projection, reg-dropout, reg-decay, train-mll, train-transfer, pool-max, arch-lstm, arch-bilstm, arch-cnn, arch-coverage, arch-transformer, struct-crf, task-seqlab | 1 | Low-Resource Name Tagging Learned with Weakly Labeled Data | Yixin Cao, Zikun Hu, Tat-seng Chua, Zhiyuan Liu, Heng Ji | https://www.aclweb.org/anthology/D19-1025.pdf |
| 2019 | EMNLP | # optim-adam, optim-projection, reg-patience, reg-decay, arch-att, arch-coverage, arch-subword, pre-bert, task-seqlab | 13 | Fine-Grained Analysis of Propaganda in News Article | Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, Rostislav Petrov, Preslav Nakov | https://www.aclweb.org/anthology/D19-1565.pdf |
| 2019 | EMNLP | # optim-adam, optim-projection, reg-dropout, reg-stopping, reg-decay, reg-labelsmooth, arch-rnn, arch-att, arch-selfatt, arch-coverage, arch-subword, arch-transformer, task-lm, task-seq2seq, task-alignment | 0 | Jointly Learning to Align and Translate with Transformer Models | Sarthak Garg, Stephan Peitz, Udhyakumar Nallasamy, Matthias Paulik | https://www.aclweb.org/anthology/D19-1453.pdf |
| 2019 | EMNLP | # optim-sgd, reg-decay, train-transfer, arch-lstm, arch-subword, search-beam, task-seq2seq, task-alignment | 0 | HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation | Brian Thompson, Rebecca Knowles, Xuan Zhang, Huda Khayrallah, Kevin Duh, Philipp Koehn | https://www.aclweb.org/anthology/D19-1142.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-stopping, reg-norm, reg-decay, arch-lstm, arch-bilstm, arch-bilinear, pre-word2vec, pre-glove, pre-elmo, pre-bert, task-lm, task-seq2seq, task-relation | 1 | Designing and Interpreting Probes with Control Tasks | John Hewitt, Percy Liang | https://www.aclweb.org/anthology/D19-1275.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, train-transfer, arch-rnn, arch-att, arch-selfatt, arch-memo, arch-subword, arch-transformer, pre-word2vec, pre-glove, pre-elmo, pre-bert, loss-nce, task-textpair, task-alignment | 0 | A Gated Self-attention Memory Network for Answer Selection | Tuan Lai, Quan Hung Tran, Trung Bui, Daisuke Kihara | https://www.aclweb.org/anthology/D19-1610.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, norm-layer, train-mll, pool-mean, arch-att, arch-selfatt, arch-transformer, comb-ensemble, pre-bert, task-spanlab, task-lm, task-seq2seq | 0 | Cross-Lingual Machine Reading Comprehension | Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, Guoping Hu | https://www.aclweb.org/anthology/D19-1169.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-decay, norm-layer, arch-rnn, arch-lstm, arch-att, arch-selfatt, arch-subword, arch-transformer, search-beam, pre-bert, task-textclass, task-seqlab, task-lm, task-seq2seq | 0 | Subword Language Model for Query Auto-Completion | Gyuwan Kim | https://www.aclweb.org/anthology/D19-1507.pdf |
| 2019 | EMNLP | # optim-adam, init-glorot, reg-dropout, reg-decay, train-mll, train-transfer, pool-max, arch-lstm, arch-att, arch-selfatt, arch-bilinear, arch-subword, arch-transformer, pre-elmo, pre-bert, struct-crf, task-textclass, task-textpair, task-seqlab, task-spanlab, task-lm, task-seq2seq, task-cloze, task-relation | 22 | Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT | Shijie Wu, Mark Dredze | https://www.aclweb.org/anthology/D19-1077.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, train-augment, arch-att, comb-ensemble, pre-bert, task-textclass, task-textpair, task-spanlab, task-lm, task-relation | 0 | CFO: A Framework for Building Production NLP Systems | Rishav Chakravarti, Cezar Pendus, Andrzej Sakrajda, Anthony Ferritto, Lin Pan, Michael Glass, Vittorio Castelli, J William Murdock, Radu Florian, Salim Roukos, Avi Sil | https://www.aclweb.org/anthology/D19-3006.pdf |
| 2019 | EMNLP | # optim-adam, optim-projection, reg-dropout, reg-decay, arch-rnn, arch-lstm, arch-gru, arch-att, arch-memo, latent-vae, latent-topic, loss-svd, task-lm, task-seq2seq | 0 | Adaptive Parameterization for Neural Dialogue Generation | Hengyi Cai, Hongshen Chen, Cheng Zhang, Yonghao Song, Xiaofang Zhao, Dawei Yin | https://www.aclweb.org/anthology/D19-1188.pdf |
| 2019 | EMNLP | # optim-adam, init-glorot, reg-dropout, reg-decay, train-mtl, pool-max, arch-rnn, arch-lstm, arch-bilstm, arch-gnn, arch-att, pre-fasttext, pre-glove, task-textclass | 0 | Text Level Graph Neural Network for Text Classification | Lianzhe Huang, Dehong Ma, Sujian Li, Xiaodong Zhang, Houfeng Wang | https://www.aclweb.org/anthology/D19-1345.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, pool-max, arch-gcnn, arch-cnn, arch-att, pre-glove, task-textclass, task-condlm, task-seq2seq | 0 | Hierarchical Text Classification with Reinforced Label Assignment | Yuning Mao, Jingjing Tian, Jiawei Han, Xiang Ren | https://www.aclweb.org/anthology/D19-1042.pdf |
| 2019 | EMNLP | # optim-amsgrad, reg-dropout, reg-decay, train-transfer, arch-lstm, arch-bilstm, arch-cnn, arch-coverage, comb-ensemble, search-beam, task-relation | 0 | A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection | Kurt Junshean Espinosa, Makoto Miwa, Sophia Ananiadou | https://www.aclweb.org/anthology/D19-1381.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-decay, train-mll, train-transfer, arch-lstm, arch-att, arch-subword, arch-transformer, search-beam, task-lm, task-seq2seq | 1 | The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English | Francisco Guzmán, Peng-Jen Chen, Myle Ott, Juan Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, Marc’Aurelio Ranzato | https://www.aclweb.org/anthology/D19-1632.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, arch-lstm, arch-att, arch-selfatt, arch-transformer, pre-bert, task-lm | 1 | Attending to Future Tokens for Bidirectional Sequence Generation | Carolin Lawrence, Bhushan Kotnis, Mathias Niepert | https://www.aclweb.org/anthology/D19-1001.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, arch-rnn, arch-gru, arch-att, pre-glove, task-seq2seq | 0 | Who Is Speaking to Whom? Learning to Identify Utterance Addressee in Multi-Party Conversations | Ran Le, Wenpeng Hu, Mingyue Shang, Zhenjun You, Lidong Bing, Dongyan Zhao, Rui Yan | https://www.aclweb.org/anthology/D19-1199.pdf |
| 2019 | EMNLP | # reg-dropout, reg-decay, reg-labelsmooth, train-mll, arch-rnn, arch-lstm, arch-att, arch-subword, arch-transformer, pre-bert, task-textclass, task-lm, task-seq2seq | 2 | MultiFiT: Efficient Multi-lingual Language Model Fine-tuning | Julian Eisenschlos, Sebastian Ruder, Piotr Czapla, Marcin Kadras, Sylvain Gugger, Jeremy Howard | https://www.aclweb.org/anthology/D19-1572.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-decay, train-mtl, arch-rnn, arch-lstm, arch-cnn, arch-att, pre-word2vec, task-textclass | 0 | Using Clinical Notes with Time Series Data for ICU Management | Swaraj Khadanga, Karan Aggarwal, Shafiq Joty, Jaideep Srivastava | https://www.aclweb.org/anthology/D19-1678.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-decay, arch-att, pre-elmo, loss-svd | 1 | An Attentive Fine-Grained Entity Typing Model with Latent Type Representation | Ying Lin, Heng Ji | https://www.aclweb.org/anthology/D19-1641.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, norm-gradient, train-transfer, arch-rnn, arch-lstm, arch-bilstm, arch-cnn, arch-att, arch-coverage, nondif-reinforce, task-extractive, task-spanlab, task-condlm, task-seq2seq | 0 | Reading Like HER: Human Reading Inspired Extractive Summarization | Ling Luo, Xiang Ao, Yan Song, Feiyang Pan, Min Yang, Qing He | https://www.aclweb.org/anthology/D19-1300.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, norm-gradient, arch-gnn, arch-att, arch-selfatt, arch-transformer, pre-bert, task-spanlab, task-tree | 0 | NumNet: Machine Reading Comprehension with Numerical Reasoning | Qiu Ran, Yankai Lin, Peng Li, Jie Zhou, Zhiyuan Liu | https://www.aclweb.org/anthology/D19-1251.pdf |
| 2019 | EMNLP | # optim-adam, reg-decay, arch-lstm, arch-cnn, pre-glove, task-textclass | 0 | Learning Only from Relevant Keywords and Unlabeled Documents | Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin, Dittaya Wanvarie, Masashi Sugiyama | https://www.aclweb.org/anthology/D19-1411.pdf |
| 2019 | EMNLP | # optim-sgd, reg-dropout, reg-decay, arch-rnn, arch-lstm, arch-bilstm, arch-att, task-lm, task-seq2seq | 3 | Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training | Hila Gonen, Yoav Goldberg | https://www.aclweb.org/anthology/D19-1427.pdf |
| 2019 | EMNLP | # optim-sgd, optim-adam, reg-dropout, reg-decay, norm-gradient, arch-rnn, arch-lstm, arch-bilstm, arch-cnn, pre-glove, pre-elmo, pre-bert, struct-crf, task-seqlab, task-lm, meta-arch | 0 | Improved Differentiable Architecture Search for Language Modeling and Named Entity Recognition | Yufan Jiang, Chi Hu, Tong Xiao, Chunliang Zhang, Jingbo Zhu | https://www.aclweb.org/anthology/D19-1367.pdf |
| 2019 | EMNLP | # optim-adam, reg-dropout, reg-decay, norm-layer, train-mll, train-parallel, arch-rnn, arch-att, arch-subword, arch-transformer, search-greedy, search-beam, pre-bert, task-lm, task-seq2seq, task-cloze | 2 | Mask-Predict: Parallel Decoding of Conditional Masked Language Models | Marjan Ghazvininejad, Omer Levy, Yinhan Liu, Luke Zettlemoyer | https://www.aclweb.org/anthology/D19-1633.pdf |
| 2019 | NAA-CL | # optim-sgd, optim-adam, optim-adadelta, reg-decay, arch-lstm, arch-recnn, arch-treelstm, arch-att, arch-coverage, search-beam, pre-glove, struct-cfg, nondif-reinforce, latent-vae, task-textpair, task-lm, task-condlm | 5 | Cooperative Learning of Disjoint Syntax and Semantics | Serhii Havrylov, Germán Kruszewski, Armand Joulin | https://www.aclweb.org/anthology/N19-1115.pdf |
| 2019 | NAA-CL | # optim-adam, reg-dropout, reg-decay, train-transfer, arch-rnn, arch-att, arch-selfatt, arch-subword, arch-transformer, comb-ensemble, search-beam, task-spanlab, task-seq2seq | 0 | Online Distilling from Checkpoints for Neural Machine Translation | Hao-Ran Wei, Shujian Huang, Ran Wang, Xin-yu Dai, Jiajun Chen | https://www.aclweb.org/anthology/N19-1192.pdf |
| 2019 | NAA-CL | # optim-adam, reg-stopping, reg-decay, train-active, arch-lstm, pre-word2vec, latent-vae, task-textclass, task-seqlab | 0 | Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks | Maolin Li, Arvid Fahlström Myrman, Tingting Mu, Sophia Ananiadou | https://www.aclweb.org/anthology/N19-1295.pdf |
| 2019 | NAA-CL | # optim-adam, reg-dropout, reg-decay, norm-batch, train-mtl, train-mll, train-transfer, arch-rnn, arch-lstm, arch-att, arch-memo, arch-subword, search-beam, task-lm, task-seq2seq | 23 | Pre-training on high-resource speech recognition improves low-resource speech-to-text translation | Sameer Bansal, Herman Kamper, Karen Livescu, Adam Lopez, Sharon Goldwater | https://www.aclweb.org/anthology/N19-1006.pdf |
| 2019 | NAA-CL | # optim-sgd, optim-projection, reg-dropout, reg-decay, norm-gradient, arch-rnn, arch-lstm, arch-bilstm, arch-att, arch-coverage, pre-glove, pre-elmo, pre-bert, struct-crf, latent-vae, task-seqlab, task-lm, task-seq2seq | 2 | Knowledge-Augmented Language Model and Its Application to Unsupervised Named-Entity Recognition | Angli Liu, Jingfei Du, Veselin Stoyanov | https://www.aclweb.org/anthology/N19-1117.pdf |
| 2019 | NAA-CL | # optim-adadelta, reg-decay, train-mtl, arch-rnn, arch-att, pre-word2vec, struct-crf, latent-vae, latent-topic, task-textclass, task-relation | 0 | A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification | Ziqian Zeng, Wenxuan Zhou, Xin Liu, Yangqiu Song | https://www.aclweb.org/anthology/N19-1036.pdf |
| 2019 | NAA-CL | # reg-dropout, reg-decay, train-mtl, arch-rnn, arch-att, arch-selfatt, arch-copy, arch-transformer, comb-ensemble, pre-glove, pre-elmo, pre-bert, task-lm, task-seq2seq, task-tree | 20 | Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data | Wei Zhao, Liang Wang, Kewei Shen, Ruoyu Jia, Jingming Liu | https://www.aclweb.org/anthology/N19-1014.pdf |
| 2019 | NAA-CL | # optim-adam, reg-decay, train-augment, arch-lstm, arch-bilstm, arch-gru, arch-bigru, arch-att, arch-selfatt, comb-ensemble, pre-glove | 0 | On Knowledge distillation from complex networks for response prediction | Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy | https://www.aclweb.org/anthology/N19-1382.pdf |
| 2019 | NAA-CL | # optim-adam, reg-dropout, reg-decay, train-transfer, train-augment, arch-lstm, arch-bilstm, arch-att, arch-selfatt, arch-coverage, arch-transformer, comb-ensemble, pre-glove, pre-skipthought, pre-elmo, pre-bert, struct-crf, task-textclass, task-textpair, task-seqlab, task-spanlab, task-lm, task-seq2seq, task-cloze | 3209 | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova | https://www.aclweb.org/anthology/N19-1423.pdf |