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https://github.com/ha-lins/metalearning4nlp-papers

A list of recent papers about Meta / few-shot learning methods applied in NLP areas.
https://github.com/ha-lins/metalearning4nlp-papers

dialogue-systems few-shot-learning low-resource meta-learning nlp papers-collection semantic-parsing

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A list of recent papers about Meta / few-shot learning methods applied in NLP areas.

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# Meta learning for NLP - Papers

A list of recent papers about Meta / few-shot learning methods applied in NLP areas.



## Call for Contributions

Contributions are welcomed, you are encouraged to:

- Open an issue and send me the paper info

- Directly pull request



## Taxonomy in Applications



### Fundamental NLP Tasks

* ### Semantic Parsing 

1. **Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing.** *Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin

.* ***ACL 2019***. [[pdf](https://arxiv.org/pdf/1906.07108.pdf)] [[code](https://github.com/microsoft/PointerSQL)]



2. **Natural Language to Structured Query Generation via Meta-Learning.** *Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen-tau Yih, Xiaodong He.* ***NAACL 2018[short]***. [[pdf](https://www.aclweb.org/anthology/N18-2115/)] [[code](https://github.com/microsoft/PointerSQL)]



3. **Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning.** *Yibo Sun, Duyu Tang, Nan Duan, Yeyun Gong, Xiaocheng Feng, Bing Qin, Daxin Jiang.* ***AAAI 2020***. [[pdf](https://www.aaai.org/Papers/AAAI/2020GB/AAAI-SunY.6672.pdf)]



4. **Hypernymy Detection for Low-Resource Languages via Meta Learning.** *Changlong Yu, Jialong Han, Haisong Zhang, Wilfred Ng.* ***ACL 2020[short]***. [[pdf](https://www.aclweb.org/anthology/2020.acl-main.336.pdf)] [[code](https://github.com/ccclyu/metaHypernymy)]



* ### Named Entity Recognition

1. **Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources.** *Qianhui Wu, Zijia Lin, Guoxin Wang, Hui Chen, Börje F. Karlsson, Biqing Huang, Chin-Yew Lin.* ***AAAI 2020***. [[pdf](https://arxiv.org/pdf/1911.06161.pdf)]



### Dialog System

1. **Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks.** *Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang* ***ACL 2020***. [[pdf](https://arxiv.org/pdf/1910.14326.pdf)][[code](https://github.com/zequnl/CMAML)]



2. **Meta-Reinforced Multi-Domain State Generator for Dialogue Systems.** *Yi Huang, Junlan Feng, Min Hu, Xiaoting Wu, Xiaoyu Du, Shuo Ma* ***ACL 2020***. [[pdf](https://www.aclweb.org/anthology/2020.acl-main.636.pdf)]



3. **Learning Low-Resource End-To-End Goal-Oriented Dialog for Fast and Reliable System Deployment.** *Yinpei Dai, Hangyu Li, Chengguang Tang, Yongbin Li, Jian Sun, Xiaodan Zhu* ***ACL 2020[short]***. [[pdf](https://www.aclweb.org/anthology/2020.acl-main.57.pdf)]



4. **Domain Adaptive Dialog Generation via Meta Learning.** *Kun Qian, Zhou Yu.* ***ACL 2019***. [[pdf](https://www.aclweb.org/anthology/P19-1253/)] [[code](https://github.com/qbetterk/DAML)]



5. **Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems.** *Fei Mi, Minlie Huang, Jiyong Zhang, Boi Faltings.* ***IJCAI 2019***. [[pdf](https://arxiv.org/abs/1905.05644)] 



6. **Personalizing Dialogue Agents via Meta-Learning.** *Zhaojiang Lin, Andrea Madotto, Chien-Sheng Wu, Pascale Fung.* ***ACL 2019[short]***. [[pdf](https://www.aclweb.org/anthology/P19-1542.pdf)] [[code](https://github.com/HLTCHKUST/PAML)]



7. **Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning.** *Yifan Gao, Piji Li, Wei Bi, Xiaojiang Liu, Michael R. Lyu, Irwin King.* ***EMNLP 2020[fingdings]***. [[pdf](https://arxiv.org/pdf/2010.01495.pdf)]



8. **Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation.** *Shuai Lin, Pan Zhou, Xiaodan Liang, Jianheng Tang, Ruihui Zhao, Ziliang Chen, Liang Lin.* ***AAAI 2021***. [[pdf](https://arxiv.org/abs/2012.11988.pdf)][[code](https://github.com/ha-lins/GEML-MDG)]



### Classification

1. **Dynamic Memory Induction Networks for Few-Shot Text Classification.** *Ruiying Geng, Binhua Li, Yongbin Li, Jian Sun, Xiaodan Zhu.* ***ACL 2020***. [[pdf](https://arxiv.org/pdf/2005.05727.pdf)]



2. **Few-shot Text Classification with Distributional Signatures.** *Yujia Bao, Menghua Wu, Shiyu Chang and Regina Barzilay.* ***ICLR 2020***. [[pdf](https://arxiv.org/abs/1908.06039)] [[code](https://github.com/YujiaBao/Distributional-Signatures)]



3. **Induction Networks for Few-Shot Text Classification.** *Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian, Jian Sun.* ***EMNLP 2019***. [[pdf](https://arxiv.org/pdf/1902.10482.pdf)] 



4. **Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification.** *Jiawei Wu, Wenhan Xiong, William Yang Wang.* ***EMNLP 2019***. [[pdf](https://www.aclweb.org/anthology/D19-1444.pdf)] 



5. **Model-Agnostic Meta-Learning for Relation Classification with Limited Supervision.** *Abiola Obamuyide, Andreas Vlachos.* ***ACL 2019[short]***. [[pdf](https://www.aclweb.org/anthology/P19-1589/)] 



6. **Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks.** *Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum.* ***EMNLP 2020***. [[pdf](https://arxiv.org/pdf/2009.08445.pdf)]



### Knowledge Graph



1. **Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs.** *Mingyang Chen, Wen Zhang, Wei Zhang, Qiang Chen, Huajun Chen.* ***EMNLP 2019***. [[pdf](https://www.aclweb.org/anthology/D19-1431.pdf)] [[code](https://github.com/AnselCmy/MetaR)]



2. **Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection.** *Shumin Deng, Ningyu Zhang, Jiaojian Kang, Yichi Zhang, Wei Zhang, Huajun Chen.* ***WSDM 2020***. [[pdf](https://arxiv.org/pdf/1910.11621.pdf)]



3. **Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations.** *Xin Lv, Yuxian Gu, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu.* ***EMNLP 2019[short]***. [[pdf](https://arxiv.org/pdf/1908.11513.pdf)][[code](https://github.com/THU-KEG/MetaKGR)]



### Text Emotion Distribution Learning



1. **Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach.** *Zhenjie Zhao, Xiaojuan Ma.* ***EMNLP 2019***. [[pdf](https://www.aclweb.org/anthology/D19-1408.pdf)] [[code](https://github.com/zhaozj89/EDL-Meta)](metric-based) 



### Machine Translation

1. **Meta-Learning for Low-Resource Neural Machine Translation.** *Jiatao Gu, Yong Wang, Yun Chen, Victor O. K. Li, Kyunghyun Cho.* ***EMNLP 2018***. [[pdf](https://www.aclweb.org/anthology/D18-1398.pdf)]



### NLU

1. **Investigating Meta-Learning Algorithms for Low-Resource NLU tasks.** *Zi-Yi Dou, Keyi Yu, Antonios Anastasopoulos.* ***EMNLP 2019[short]***. [[pdf](https://www.aclweb.org/anthology/D19-1112.pdf)]



2. **Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network.** *Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, Ting Liu.* ***ACL 2020[long]***. [[pdf](https://arxiv.org/abs/2006.05702)][[code](https://github.com/AtmaHou/FewShotTagging)]



### Pre-trained language models

1. **Pre-training Text Representations as Meta Learning.** *Shangwen Lv, Yuechen Wang, Daya Guo, Duyu Tang, Nan Duan, Fuqing Zhu, Ming Gong, Linjun Shou, Ryan Ma, Daxin Jiang, Guihong Cao, Ming Zhou, Songlin Hu.* ***ACL 2020[short]***. [[pdf](https://arxiv.org/pdf/2004.05568)]



2. **Meta Fine-Tuning Neural Language Models for Multi-Domain Text Mining.** *Chengyu Wang, Minghui Qiu, Jun Huang, Xiaofeng He.* ***EMNLP 2020***. [[pdf](https://arxiv.org/pdf/2003.13003.pdf)]



### Speech Recognition

1. **Meta-Transfer Learning for Code-Switched Speech Recognition.** *Genta Indra Winata, Samuel Cahyawijaya, Zhaojiang Lin, Zihan Liu, Peng Xu, Pascale Fung.* ***ACL 2020[Long]***. [[pdf](https://arxiv.org/pdf/2004.14228.pdf)][[code](https://github.com/audioku/meta-transfer-learning)]



2. **Meta Learning for End-to-End Low-Resource Speech Recognition.** *Jui-Yang Hsu, Yuan-Jui Chen, Hung-yi Lee.* ***ICASSP 2020***. [[pdf](https://arxiv.org/pdf/1910.12094.pdf)]



3. **Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition.** *Xiao Yubei, Ke Gong, Pan Zhou, Guolin Zheng, Xiaodan Liang and Liang Lin.* ***AAAI 2021***. [[pdf](https://arxiv.org/pdf/2012.11896.pdf)][[code](https://github.com/iamxiaoyubei/AMS)]



### Question Answer

1. **Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering.** *Ming Yan, Hao Zhang, Di Jin, Joey Tianyi Zhou.* ***ACL 2020***. [[pdf](https://www.aclweb.org/anthology/2020.acl-main.654.pdf)]



### Cross-Lingual Transfer

1. **Zero-Shot Cross-Lingual Transfer with Meta Learning.** *Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein.* ***EMNLP 2020***. [[pdf](https://arxiv.org/pdf/2003.02739.pdf)][[code](https://github.com/copenlu/X-MAML)]



2. **Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages.** *Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein.* ***EMNLP 2020***. [[pdf](Coming soon)]



3. **On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment.** *Zirui Wang, Zachary C. Lipton, Yulia Tsvetkov.* ***EMNLP 2020***. [[pdf](https://arxiv.org/pdf/2010.03017.pdf)][[code](https://github.com/iedwardwangi/MetaAdapter)]