Year |
Conf. |
Topic |
Cited |
Paper |
Authors |
Url |
2019 |
ACL |
# optim-adam, reg-dropout, train-mtl, arch-rnn, arch-lstm, arch-bilstm, arch-coverage, arch-energy, comb-ensemble, search-beam, task-seq2seq, task-relation, task-tree |
2 |
Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies |
Shuhei Kurita, Anders Søgaard |
https://www.aclweb.org/anthology/P19-1232.pdf |
2019 |
ACL |
# optim-adam, reg-dropout, activ-tanh, pool-max, arch-rnn, arch-lstm, arch-bilstm, arch-cnn, arch-att, arch-memo, arch-bilinear, arch-energy, search-viterbi, struct-crf, latent-topic, task-seqlab, task-lm |
1 |
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction |
Huaishao Luo, Tianrui Li, Bing Liu, Junbo Zhang |
https://www.aclweb.org/anthology/P19-1056.pdf |
2019 |
ACL |
# optim-adam, init-glorot, reg-dropout, reg-labelsmooth, norm-layer, arch-rnn, arch-lstm, arch-treelstm, arch-gnn, arch-cnn, arch-att, arch-selfatt, arch-residual, arch-energy, arch-transformer, search-beam, task-seq2seq |
2 |
Self-Attentional Models for Lattice Inputs |
Matthias Sperber, Graham Neubig, Ngoc-Quan Pham, Alex Waibel |
https://www.aclweb.org/anthology/P19-1115.pdf |
2019 |
ACL |
# optim-adam, optim-adadelta, init-glorot, reg-dropout, norm-gradient, train-transfer, pool-max, arch-rnn, arch-lstm, arch-gnn, arch-att, arch-energy, search-beam, pre-glove, struct-crf, nondif-minrisk, task-textclass, task-seq2seq |
3 |
Joint Type Inference on Entities and Relations via Graph Convolutional Networks |
Changzhi Sun, Yeyun Gong, Yuanbin Wu, Ming Gong, Daxin Jiang, Man Lan, Shiliang Sun, Nan Duan |
https://www.aclweb.org/anthology/P19-1131.pdf |
2019 |
ACL |
# init-glorot, arch-rnn, arch-lstm, arch-cnn, arch-att, arch-bilinear, arch-energy, comb-ensemble, pre-fasttext, pre-bert, struct-crf, task-relation |
0 |
An Empirical Investigation of Structured Output Modeling for Graph-based Neural Dependency Parsing |
Zhisong Zhang, Xuezhe Ma, Eduard Hovy |
https://www.aclweb.org/anthology/P19-1562.pdf |
2019 |
ACL |
# optim-adam, init-glorot, reg-norm, arch-cnn, arch-att, arch-energy, pre-glove |
0 |
Unsupervised Information Extraction: Regularizing Discriminative Approaches with Relation Distribution Losses |
Étienne Simon, Vincent Guigue, Benjamin Piwowarski |
https://www.aclweb.org/anthology/P19-1133.pdf |
2019 |
EMNLP |
# optim-adam, reg-dropout, arch-lstm, arch-bilstm, arch-energy, adv-train |
0 |
Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog |
Ryuichi Takanobu, Hanlin Zhu, Minlie Huang |
https://www.aclweb.org/anthology/D19-1010.pdf |
2019 |
EMNLP |
# optim-adam, arch-att, arch-selfatt, arch-energy, pre-bert, task-spanlab |
4 |
Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering |
Zhiguo Wang, Patrick Ng, Xiaofei Ma, Ramesh Nallapati, Bing Xiang |
https://www.aclweb.org/anthology/D19-1599.pdf |
2019 |
EMNLP |
# optim-adam, arch-rnn, arch-lstm, arch-gru, arch-att, arch-energy, search-sampling, pre-glove, struct-crf, task-textpair, task-lm, task-condlm, task-seq2seq |
0 |
Autoregressive Text Generation Beyond Feedback Loops |
Florian Schmidt, Stephan Mandt, Thomas Hofmann |
https://www.aclweb.org/anthology/D19-1338.pdf |
2019 |
NAA-CL |
# optim-sgd, optim-adam, init-glorot, reg-dropout, train-transfer, arch-rnn, arch-lstm, arch-gru, arch-cnn, arch-att, arch-gating, arch-energy, search-viterbi, pre-word2vec, pre-skipthought, struct-hmm, struct-crf, adv-train, task-textclass, task-seq2seq |
0 |
Adaptation of Hierarchical Structured Models for Speech Act Recognition in Asynchronous Conversation |
Tasnim Mohiuddin, Thanh-Tung Nguyen, Shafiq Joty |
https://www.aclweb.org/anthology/N19-1134.pdf |
2019 |
NAA-CL |
# arch-rnn, arch-lstm, arch-coverage, arch-energy, struct-crf, task-seq2seq |
1 |
Lost in Interpretation: Predicting Untranslated Terminology in Simultaneous Interpretation |
Nikolai Vogler, Craig Stewart, Graham Neubig |
https://www.aclweb.org/anthology/N19-1010.pdf |
2019 |
NAA-CL |
# optim-adam, reg-dropout, norm-gradient, train-mll, train-augment, arch-rnn, arch-lstm, arch-att, arch-energy, task-condlm, task-seq2seq, task-relation |
7 |
A Simple Joint Model for Improved Contextual Neural Lemmatization |
Chaitanya Malaviya, Shijie Wu, Ryan Cotterell |
https://www.aclweb.org/anthology/N19-1155.pdf |
2019 |
NAA-CL |
# arch-rnn, arch-lstm, arch-att, arch-energy, search-beam, struct-crf, struct-cfg, loss-nce, task-condlm, task-seq2seq, task-relation |
0 |
An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search |
Kartik Goyal, Chris Dyer, Taylor Berg-Kirkpatrick |
https://www.aclweb.org/anthology/N19-1171.pdf |