ConVEx: Data-Efficient and Few-Shot Slot Labeling
暂无分享,去创建一个
[1] Zhihan Zhou,et al. Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network , 2020, ACL.
[2] Steve J. Young,et al. Still talking to machines (cognitively speaking) , 2010, INTERSPEECH.
[3] Armen Aghajanyan,et al. Pre-training via Paraphrasing , 2020, NeurIPS.
[4] Stefan Ultes,et al. MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling , 2018, EMNLP.
[5] Matthew Henderson,et al. Efficient Natural Language Response Suggestion for Smart Reply , 2017, ArXiv.
[6] Thomas Wolf,et al. Transfer Learning in Natural Language Processing , 2019, NAACL.
[7] Vladimir Vlasov,et al. DIET: Lightweight Language Understanding for Dialogue Systems , 2020, ArXiv.
[8] Maxine Eskénazi,et al. Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models , 2019, NAACL.
[9] Veselin Stoyanov,et al. Unsupervised Cross-lingual Representation Learning at Scale , 2019, ACL.
[10] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[11] Andrew McCallum,et al. Energy and Policy Considerations for Deep Learning in NLP , 2019, ACL.
[12] Raghav Gupta,et al. Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset , 2020, AAAI.
[13] Steve J. Young,et al. Talking to machines (statistically speaking) , 2002, INTERSPEECH.
[14] Matthew Henderson,et al. Training Neural Response Selection for Task-Oriented Dialogue Systems , 2019, ACL.
[15] Omer Levy,et al. RoBERTa: A Robustly Optimized BERT Pretraining Approach , 2019, ArXiv.
[16] Matthew Henderson,et al. A Repository of Conversational Datasets , 2019, Proceedings of the First Workshop on NLP for Conversational AI.
[17] Matthew Henderson,et al. ConveRT: Efficient and Accurate Conversational Representations from Transformers , 2020, EMNLP.
[18] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[19] Frank Hutter,et al. SGDR: Stochastic Gradient Descent with Warm Restarts , 2016, ICLR.
[20] Omer Levy,et al. Few-Shot Question Answering by Pretraining Span Selection , 2021, ACL/IJCNLP.
[21] Samy Bengio,et al. Tensor2Tensor for Neural Machine Translation , 2018, AMTA.
[22] Yiming Yang,et al. XLNet: Generalized Autoregressive Pretraining for Language Understanding , 2019, NeurIPS.
[23] Nan Hua,et al. Universal Sentence Encoder for English , 2018, EMNLP.
[24] Mark Chen,et al. Language Models are Few-Shot Learners , 2020, NeurIPS.
[25] Dilek Z. Hakkani-Tür,et al. DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue , 2020, ArXiv.
[26] Javier Snaider,et al. Conversational Contextual Cues: The Case of Personalization and History for Response Ranking , 2016, ArXiv.
[27] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[28] Matthew Henderson,et al. Efficient Intent Detection with Dual Sentence Encoders , 2020, NLP4CONVAI.
[29] Jason Weston,et al. Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring , 2019 .
[30] Vishrav Chaudhary,et al. CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data , 2019, LREC.
[31] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[32] Matthew Henderson,et al. Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations , 2020, ACL.
[33] Kevin Gimpel,et al. Gaussian Error Linear Units (GELUs) , 2016 .
[34] Matthew Henderson,et al. The Second Dialog State Tracking Challenge , 2014, SIGDIAL Conference.
[35] Sung Whan Yoon,et al. TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning , 2019, ICML.
[36] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[37] Varvara Logacheva,et al. Few-shot classification in named entity recognition task , 2018, SAC.
[38] Francesco Caltagirone,et al. Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces , 2018, ArXiv.
[39] Yi Zhang,et al. Learning to Classify Intents and Slot Labels Given a Handful of Examples , 2020, NLP4CONVAI.
[40] Andrew McCallum,et al. An Introduction to Conditional Random Fields , 2010, Found. Trends Mach. Learn..
[41] Gokhan Tur,et al. Spoken Language Understanding: Systems for Extracting Semantic Information from Speech , 2011 .
[42] Jason D. Williams,et al. Web-style ranking and SLU combination for dialog state tracking , 2014, SIGDIAL Conference.
[43] Oren Etzioni,et al. Green AI , 2019, Commun. ACM.