Year	Conf.	Topic	Cited	Paper	Authors	Url
2019	ACL	# optim-adam, reg-dropout, train-mtl, train-transfer, pool-max, arch-rnn, arch-lstm, arch-bilstm, arch-att, arch-selfatt, pre-elmo, loss-svd, task-textclass, task-textpair, task-lm, task-seq2seq, meta-arch	1	Continual and Multi-Task Architecture Search	Ramakanth Pasunuru, Mohit Bansal	https://www.aclweb.org/anthology/P19-1185.pdf
2019	ACL	# reg-dropout, norm-batch, norm-gradient, activ-relu, arch-rnn, arch-lstm, arch-gcnn, arch-att, arch-selfatt, arch-transformer, task-lm, task-seq2seq, meta-arch	194	Transformer-XL: Attentive Language Models beyond a Fixed-Length Context	Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, Ruslan Salakhutdinov	https://www.aclweb.org/anthology/P19-1285.pdf
2019	ACL	# optim-adam, reg-dropout, pool-max, comb-ensemble, adv-train, task-textclass, meta-arch	1	Incorporating Priors with Feature Attribution on Text Classification	Frederick Liu, Besim Avci	https://www.aclweb.org/anthology/P19-1631.pdf
2019	ACL	# reg-dropout, arch-lstm, arch-cnn, pre-word2vec, struct-crf, struct-cfg, meta-arch	1	AutoML Strategy Based on Grammatical Evolution: A Case Study about Knowledge Discovery from Text	Suilan Estevez-Velarde, Yoan Gutiérrez, Andrés Montoyo, Yudivián Almeida-Cruz	https://www.aclweb.org/anthology/P19-1428.pdf
2019	ACL	# optim-sgd, reg-dropout, arch-rnn, arch-lstm, arch-gcnn, arch-cnn, arch-att, arch-selfatt, arch-gating, arch-memo, arch-transformer, task-lm, task-seq2seq, task-alignment, meta-arch	1	Improving Neural Language Models by Segmenting, Attending, and Predicting the Future	Hongyin Luo, Lan Jiang, Yonatan Belinkov, James Glass	https://www.aclweb.org/anthology/P19-1144.pdf
2019	ACL	# optim-adam, arch-lstm, arch-att, arch-selfatt, arch-bilinear, arch-transformer, pre-elmo, pre-bert, task-seqlab, task-lm, task-seq2seq, task-relation, meta-arch	76	Energy and Policy Considerations for Deep Learning in NLP	Emma Strubell, Ananya Ganesh, Andrew McCallum	https://www.aclweb.org/anthology/P19-1355.pdf
2019	EMNLP	# reg-stopping, arch-lstm, arch-bilstm, arch-att, arch-coverage, pre-glove, pre-elmo, pre-bert, task-textclass, task-textpair, task-spanlab, task-lm, meta-arch	1	Show Your Work: Improved Reporting of Experimental Results	Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith	https://www.aclweb.org/anthology/D19-1224.pdf
2019	EMNLP	# optim-adam, arch-rnn, arch-lstm, arch-gru, arch-cnn, pre-glove, pre-bert, task-textclass, task-lm, task-seq2seq, meta-arch	1	RNN Architecture Learning with Sparse Regularization	Jesse Dodge, Roy Schwartz, Hao Peng, Noah A. Smith	https://www.aclweb.org/anthology/D19-1110.pdf
2019	EMNLP	# optim-adam, train-augment, arch-rnn, arch-lstm, arch-bilstm, arch-att, arch-selfatt, arch-gating, pre-glove, adv-train, task-textpair, task-spanlab, meta-arch	3	Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning	Yichen Jiang, Mohit Bansal	https://www.aclweb.org/anthology/D19-1455.pdf
2019	EMNLP	# optim-sgd, optim-adam, reg-dropout, train-active, arch-rnn, arch-lstm, arch-bilstm, arch-cnn, comb-ensemble, pre-fasttext, task-textclass, task-lm, meta-arch	0	Sampling Bias in Deep Active Classification: An Empirical Study	Ameya Prabhu, Charles Dognin, Maneesh Singh	https://www.aclweb.org/anthology/D19-1417.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	# reg-dropout, arch-rnn, arch-lstm, arch-bilstm, arch-gru, arch-att, arch-gating, arch-transformer, pre-glove, pre-elmo, pre-bert, struct-crf, task-textclass, task-seqlab, task-seq2seq, meta-arch	1	NeuronBlocks: Building Your NLP DNN Models Like Playing Lego	Ming Gong, Linjun Shou, Wutao Lin, Zhijie Sang, Quanjia Yan, Ze Yang, Feixiang Cheng, Daxin Jiang	https://www.aclweb.org/anthology/D19-3028.pdf