SlowGuess/NAACL_2022_OCR huggingface dataset:
Zi-Yi Dou, Keyi Yu, and Antonios Anastasopoulos. 2019. Investigating meta-learning algorithms for low-resource natural language understanding tasks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Benjamin Ehret, Christian Henning, Maria Cervera, Alexander Meulemans, Johannes Von Oswald, and Benjamin F Grewe. 2021. Continual learning in recurrent neural networks. In International Conference on Learning Representations.
Ryan Eloff, Herman A. Engelbrecht, and Herman Kamper. 2019. Multimodal one-shot learning of speech and images. In ICASSP.
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In ICML.
Chelsea Finn, Aravind Rajeswaran, Sham Kakade, and Sergey Levine. 2019. Online meta-learning. In ICML.
Tianyu Gao, Xu Han, Zhiyuan Liu, and Maosong Sun. 2019a. Hybrid attention-based prototypical networks for noisy few-shot relation classification. In AAAI.
Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. 2019b. FewRel 2.0: Towards more challenging few-shot relation classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Jezabel Garcia, Federica Freddi, Jamie McGowan, Tim Nieradzik, Feng-Ting Liao, Ye Tian, Da-shan Shiu, and Alberto Bernacchia. 2021. Cross-lingual transfer with MAML on trees. In Proceedings of the Second Workshop on Domain Adaptation for NLP.
Ruiying Geng, Binhua Li, Yongbin Li, Jian Sun, and Xiaodan Zhu. 2020. Dynamic memory induction networks for few-shot text classification. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian, and Jian Sun. 2019. Induction networks for few-shot text classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Jiatao Gu, Yong Wang, Yun Chen, Victor O. K. Li, and Kyunghyun Cho. 2018. Meta-learning for low-resource neural machine translation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.
Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, and Jian Yin. 2019. Coupling retrieval and meta-learning for context-dependent semantic parsing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Niels van der Heijden, Helen Yannakoudakis, Pushkar Mishra, and Ekaterina Shutova. 2021. Multilingual and cross-lingual document classification: A meta-learning approach. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume.
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531.
Nithin Holla, Pushkar Mishra, Helen Yannakoudakis, and Ekaterina Shutova. 2020. Learning to learn to disambiguate: Meta-learning for few-shot word sense disambiguation. In *Findings of the Association for Computational Linguistics: EMNLP* 2020.
Timothy M Hospedales, Antreas Antoniou, Paul Micaelli, and Amos J. Storkey. 2021. Meta-learning in neural networks: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 1-1.
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, and Ting Liu. 2020. Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Jui-Yang Hsu, Yuan-Jui Chen, and Hung yi Lee. 2020. Meta learning for end-to-end low-resource speech recognition. In ICASSP.
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan First, and Melvin Johnson. 2020. Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalisation. In ICML.
Ziniu Hu, Ting Chen, Kai-Wei Chang, and Yizhou Sun. 2019. Few-shot representation learning for out-of-vocabulary words. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Yuncheng Hua, Yuan-Fang Li, Gholamreza Haffari, Guilin Qi, and Tongtong Wu. 2020. Few-shot complex knowledge base question answering via meta reinforcement learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Kuan-Po Huang, Yuan-Kuei Wu, and Hung yi Lee. 2021. Multi-accent speech separation with one shot learning. In metaNLP ACL.
Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen tau Yih, and Xiaodong He. 2018. Natural language to structured query generation via meta-learning. In NAACL.
Sung-feng Huang, Chyi-Jiunn Lin, Da-rong Liu, Yi-chen Chen, and Hung-yi Lee. 2022. Meta-TTS: Meta-learning for few-shot speaker adaptive text-to-speech. IEEE/ACM Transactions on Audio, Speech, and Language Processing.
Yi Huang, Junlan Feng, Min Hu, Xiaoting Wu, Xiaoyu Du, and Shuo Ma. 2020a. Meta-reinforced multi-domain state generator for dialogue systems. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Yi Huang, Junlan Feng, Shuo Ma, Xiaoyu Du, and Xiaoting Wu. 2020b. Towards low-resource semi-supervised dialogue generation with meta-learning. In Findings of the Association for Computational Linguistics: EMNLP 2020.
Jaesung Huh, Minjae Lee, Heesoo Heo, Seongkyu Mun, and Joon Son Chung. 2021. Metric learning for keyword spotting. In 2021 IEEE Spoken Language Technology Workshop (SLT).
Mike Huisman, Jan N. van Rijn, and Aske Plaat. 2021. A survey of deep meta-learning. In AI Review (AIRE) Journal.
Sathish Indurthi, Houjeung Han, Nikhil Kumar Lakumarapu, Beomseok Lee, Insoo Chung, Sangha Kim, and Chanwoo Kim. 2020. Data efficient direct speech-to-text translation with modality agnostic meta-learning. In ICASSP.
Yufan Jiang, Chi Hu, Tong Xiao, Chunliang Zhang, and Jingbo Zhu. 2019. Improved differentiable architecture search for language modeling and named entity recognition. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Zhen Ke, Liang Shi, Songtao Sun, Erli Meng, Bin Wang, and Xipeng Qiu. 2021. Pre-training with meta learning for Chinese word segmentation. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017. Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences, 114.
Ondrej Klejch, Joachim Fainberg, and Peter Bell. 2018. Learning to adapt: a meta-learning approach for speaker adaptation. In INTERSPEECH.
Ondrej Klejch, Joachim Fainberg, Peter Bell, and Steve Renals. 2019. Speaker adaptive training using model agnostic meta-learning. In ASRU.
Wouter M. Kouw and Marco Loog. 2021. A review of domain adaptation without target labels. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3):766-785.
Anna Langedijk, Verna Dankers, Phillip Lippe, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, and Ekaterina Shutova. 2021. Meta-learning for fast cross-lingual adaptation in dependency parsing. In arXiv.
Hung-Yi Lee, Mitra Mohtarami, Shang-Wen Li, Di Jin, Mandy Korpusik, Shuyan Dong, Ngoc Thang Vu, and Dilek Hakkani-Tur. 2021a. Proceedings of the 1st workshop on meta learning and its applications to natural language processing. In Proceedings of the 1st Workshop on Meta Learning and Its Applications to Natural Language Processing.
Hung-yi Lee, Ngoc Thang Vu, and Shang-Wen Li. 2021b. Meta learning and its applications to natural language processing. ACL-IJCNLP 2021, page 15.
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M. Hospedales. 2018. Learning to generalize: Meta-learning for domain generalization. In AAAI.
Rumeng Li, Xun Wang, and Hong Yu. 2020a. MetaMT, a meta learning method leveraging multiple domain data for low resource machine translation. Proceedings of the AAAI Conference on Artificial Intelligence, 34(05).
Yinqiao Li, Chi Hu, Yuhao Zhang, Nuo Xu, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, and Changliang Li. 2020b. Learning architectures from an extended search space for language modeling. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang, and Qiang Yang. 2020c. Learn to cross-lingual transfer with meta graph learning across heterogeneous languages. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Zhizhong Li and Derek Hoiem. 2017. Learning without forgetting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40.
David Lopez-Paz and Marc'Aurelio Ranzato. 2017. Gradient episodic memory for continual learning. In NeurIPS.
Florian Lux and Ngoc Thang Vu. 2021. Meta-learning for improving rare word recognition in end-to-end asr. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 5974-5978. IEEE.
Xin Lv, Yuxian Gu, Xu Han, Lei Hou, Juanzi Li, and Zhiyuan Liu. 2019. Adapting meta knowledge graph information for multi-hop reasoning over few-shot relations. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar, Sriram Venkatapathy, Ragav Venkatesan, and Rahul Gupta. 2020. Evaluating the effectiveness of efficient neural architecture search for sentence-pair tasks. In Proceedings of the First Workshop on Insights from Negative Results in NLP.
Andrea Madotto, Zhaojiang Lin, Chien-Sheng Wu, and Pascale Fung. 2019. Personalizing dialogue agents via meta-learning. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Christopher Manning and Hinrich Schutze. 1999. Foundations of statistical natural language processing.
Hanna Mazzawi, Xavi Gonzalvo, Aleks Kracun, Prashant Sridhar, Niranjan Subrahmanya, Ignacio Lopez Moreno, Hyun Jin Park, and Patrick Violette. 2019. Improving keyword spotting and language identification via neural architecture search at scale. In INTERSPEECH.
Michael McCloskey and Neal J Cohen. 1989. Catastrophic interference in connectionist networks: The sequential learning problem. In Psychology of Learning and Motivation, volume 24.
Stephen Merity, Bryan McCann, and Richard Socher. 2017. Revisiting activation regularization for language rnns. arXiv preprint arXiv:1708.01009.
Meryem M'hamdi, Doo Soon Kim, Franck Dernoncourt, Trung Bui, Xiang Ren, and Jonathan May. 2021. X-METRA-ADA: Cross-lingual meta-transfer learning adaptation to natural language understanding and question answering. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Fei Mi, Minlie Huang, Jiyong Zhang, and Boi Faltings. 2019. Meta-learning for low-resource natural language generation in task-oriented dialogue systems. In IJCAI.
Tomáš Mikolov, Martin Karafált, Lukáš Burget, Jan Černocký, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model. In INTERSPEECH.
Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel. 2018. A simple neural attentive meta-learner. In ICLR.
Shikhar Murty, Tatsunori B. Hashimoto, and Christopher Manning. 2021. DReCa: A general task augmentation strategy for few-shot natural language inference. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, and Tom Goldstein. 2021. Data augmentation for meta-learning. In Proceedings of the 38th International Conference on Machine Learning, volume 139 of Proceedings of Machine Learning Research, pages 8152-8161. PMLR.
Alex Nichol, Joshua Achiam, and John Schulman. 2018. On first-order meta-learning algorithms.
Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, and Isabelle Augenstein. 2020. Zero-shot cross-lingual transfer with meta learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Abiola Obamuyide and Andreas Vlachos. 2019a. Meta-learning improves lifelong relation extraction. In Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019).
Abiola Obamuyide and Andreas Vlachos. 2019b. Model-agnostic meta-learning for relation classification with limited supervision. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Cennet Oguz and Ngoc Thang Vu. 2021. Few-shot learning for slot tagging with attentive relational network. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume.
Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang, Yaliang Li, and Jun Huang. 2020. Meta-KD: A meta knowledge distillation framework for language model compression across domains. arXiv preprint arXiv:2012.01266.
German I. Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan, and Stefan Wermter. 2019. Continual lifelong learning with neural networks: A review. *Neural Networks*, 113:54-71.
Cheonbok Park, Yunwon Tae, TaeHee Kim, Soyoung Yang, Mohammad Azam Khan, Lucy Park, and Jaegul Choo. 2021. Unsupervised neural machine translation for low-resource domains via meta-learning. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers).
Archit Parnami and Minwoo Lee. 2020. Few-shot keyword spotting with prototypical networks.
Ramakanth Pasunuru and Mohit Bansal. 2019. Continual and multi-task architecture search. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Ramakanth Pasunuru and Mohit Bansal. 2020. FENAS: Flexible and expressive neural architecture search. In *Findings of the Association for Computational Linguistics: EMNLP* 2020.
Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, and Jeff Dean. 2018a. Efficient neural architecture search via parameter sharing. In ICML.
Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, and Jeff Dean. 2018b. Efficient neural architecture search via parameters sharing. In ICML.
Hieu Pham, Xinyi Wang, Yiming Yang, and Graham Neubig. 2021. Meta back-translation. In ICLR.
Kun Qian, Wei Wei, and Zhou Yu. 2021. A student-teacher architecture for dialog domain adaptation under the meta-learning setting. In AAAI.
Kun Qian and Zhou Yu. 2019. Domain adaptive dialog generation via meta learning. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019. Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv preprint arXiv:1910.10683.
Janarthanan Rajendran, Alexander Irpan, and Eric Jang. 2020. Meta-learning requires meta-augmentation. In NeurIPS.
Sachin Ravi and Hugo Larochelle. 2017. Optimization as a model for few-shot learning. In ICLR.
Haopeng Ren, Yi Cai, Xiaofeng Chen, Guohua Wang, and Qing Li. 2020. A two-phase prototypical network model for incremental few-shot relation classification. In Proceedings of the 28th International Conference on Computational Linguistics.
Gobinda Saha and Kaushik Roy. 2021. Gradient projection memory for continual learning. *ICLR*.
Erik Tjong Kim Sang and Fien De Meulder. 2003. Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition. In HLT-NAACL.
H Schütze. 1992. Dimensions of meaning. In Proceedings of the 1992 ACM/IEEE conference on Supercomputing, pages 787-796.
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell. 2018. Progress & compress: A scalable framework for continual learning. In ICML.
Joan Serrà, Santiago Pascual, and Carlos Segura. 2019. Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion. In NeurIPS.
Jiawei Sheng, Shu Guo, Zhenyu Chen, Juwei Yue, Lihong Wang, Tingwen Liu, and Hongbo Xu. 2020. Adaptive attentional network for few-shot knowledge graph completion. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Jun Shu, Qi Xie, Lixuan Yi, Qian Zhao, Sanping Zhou, Zongben Xu, and Deyu Meng. 2019. Meta-Weight-Net: Learning an explicit mapping for sample weighting. In NeurIPS.
Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitriy Pyrkin, Sergei Popov, and Artem Babenko. 2020. Editable neural networks. In ICLR.
Jake Snell, Kevin Swersky, and Richard S. Zemel. 2017. Prototypical networks for few-shot learning. In NIPS.
Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae, Alexander Pritzel, Adrià Puigdomènech Badia, Benigno Uria, Oriol Vinyals, Demis Hassabis, Razvan Pascanu, and Charles Blundell. 2018. Memory-based parameter adaptation. In ICLR.
Fan-Keng Sun, Cheng-Hao Ho, and Hung-Yi Lee. 2019a. LAMOL: Language MOdeling for Lifelong Language Learning. In ICLR.
Jingyuan Sun, Shaonan Wang, and Chengqing Zong. 2018. Memory, show the way: Memory based few shot word representation learning. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.
Shengli Sun, Qingfeng Sun, Kevin Zhou, and Tengchao Lv. 2019b. Hierarchical attention prototypical networks for few-shot text classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, and Denny Zhou. 2020. MobileBERT: a compact task-agnostic BERT for resource-limited devices. In ACL.
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H.S. Torr, and Timothy M. Hospedales. 2018. Learning to compare: Relation network for few-shot learning. In CVPR.
Dídac Surís, Dave Epstein, Heng Ji, Shih-Fu Chang, and Carl Vondrick. 2019. Learning to learn words from narrated video. In ECCV.
Ming Tan, Yang Yu, Haoyu Wang, Dakuo Wang, Saloni Potdar, Shiyu Chang, and Mo Yu. 2019. Out-of-Domain detection for low-resource text classification tasks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Ishan Tarunesh, Sushil Khyalia, Vishwajeet Kumar, Ganesh Ramakrishnan, and Preethi Jyothi. 2021. Meta-learning for effective multi-task and multilingual modelling. In EACL.
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, and Hugo Larochelle. 2020. Meta-Dataset: A dataset of datasets for learning to learn from few examples. In International Conference on Learning Representations.
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra. 2016. Matching networks for one shot learning. In NIPS.
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2018. GLUE: A multitask benchmark and analysis platform for natural language understanding. In Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP.
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2019a. Glue: A multi-task benchmark and analysis platform for natural language understanding. In ICLR.
Bailin Wang, Mirella Lapata, and Ivan Titov. 2021a. Meta-learning for domain generalization in semantic parsing. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, and Song Han. 2020a. HAT: Hardware-aware transformers for efficient natural language processing. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Lingxiao Wang, Kevin Huang, Tengyu Ma, Quanquan Gu, and Jing Huang. 2021b. Variance-reduced first-order meta-learning for natural language processing tasks. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Xinyi Wang, Yulia Tsvetkov, and Graham Neubig. 2020b. Balancing training for multilingual neural machine translation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Zihao Wang, Kwunping Lai, Piji Li, Lidong Bing, and Wai Lam. 2019b. Tackling long-tailed relations and uncommon entities in knowledge graph completion. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Zirui Wang, Sanket Vaibhav Mehta, Barnabas Poczos, and Jaime Carbonell. 2020c. Efficient meta lifelong-learning with limited memory. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Genta Indra Winata, Samuel Cahyawijaya, Zhaojiang Lin, Zihan Liu, Peng Xu, and Pascale Fung. 2020a. Meta-transfer learning for code-switched speech recognition. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
Genta Indra Winata, Samuel Cahyawijaya, Zihan Liu, Zhaojiang Lin, Andrea Madotto, Peng Xu, and Pascale Fung. 2020b. Learning fast adaptation on cross-accented speech recognition. In INTERSPEECH.
Jiawei Wu, Wenhan Xiong, and William Yang Wang. 2019. Learning to learn and predict: A meta-learning approach for multi-label classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
Qianhui Wu, Zijia Lin, Guoxin Wang, Hui Chen, Borje F. Karlsson, Biqing Huang, and Chin-Yew Lin. 2020. Enhanced meta-learning for cross-lingual named entity recognition with minimal resources. In AAAI.
Tongtong Wu, Xuekai Li, Yuan-Fang Li, Reza Haffari, Guilin Qi, Yujin Zhu, and Guoqiang Xu. 2021a. Curriculum-meta learning for order-robust continual relation extraction. In AAAI.
Yuan-Kuei Wu, Kuan-Po Huang, Yu Tsao, and Hung-yi Lee. 2021b. One shot learning for speech separation. In ICASSP.