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With the recent surge of NLP technologies in the financial domain, banks and other financial entities have adopted virtual agents (VA) to assist customers.
Few-shot intent detection via contrastive pre-training and fine-tuning
Jianguo Zhang, Trung Bui, Seunghyun Yoon, Xiang Chen, Zhiwei Liu, Congying Xia, Quan Hung Tran, Walter Chang, and Philip Yu. 2021b · 1912
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Short text clustering via convolutional neural networks
Jiaming Xu, Peng Wang, Guanhua Tian, Bo Xu, Jun Zhao, Fangyuan Wang, and Hongwei Hao. 2015 · 2015
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Unsupervised dialogue act induction using Gaussian mixtures
Tomáš Brychcín and Pavel Král. 2017 · 2017
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DOC: Deep open classification of text documents
Lei Shu, Hu Xu, and Bing Liu. 2017 · 2017
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Zero-shot user intent detection via capsule neural networks
Congying Xia, Chenwei Zhang, Xiaohui Yan, Yi Chang, and Philip Yu. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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A novel bi-directional interrelated model for joint intent detection and slot filling
Haihong E, Peiqing Niu, Zhongfu Chen, and Meina Song. 2019 · 2019
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On a chatbot conducting a virtual dialogue in financial domain
Boris Galitsky and Dmitry Ilvovsky. 2019 · 2019
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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An evaluation dataset for intent classification and out-of-scope prediction
Stefan Larson, Anish Mahendran, Joseph J. Peper, Christopher Clarke, Andrew Lee, Parker Hill, Jonathan K. Kummerfeld, Kevin Leach, Michael A. Laurenzano, Lingjia Tang, and Jason Mars. 2019 · 2019
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Deep unknown intent detection with margin loss
Ting-En Lin and Hua Xu. 2019 · 2019
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Energy and policy considerations for deep learning in NLP
Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019 · 2019
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Joint slot filling and intent detection via capsule neural networks
Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, and Philip Yu. 2019 · 2019
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Efficient intent detection with dual sentence encoders
Iñigo Casanueva, Tadas Temcinas, Daniela Gerz, Matthew Henderson, and Ivan Vulic. 2020 · 2020
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2020
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang. 2021 · 2021
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A survey of the usages of deep learning for natural language processing
Daniel W. Otter, Julian R. Medina, and Jugal K. Kalita. 2021 · 2021
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A survey of joint intent detection and slot-filling models in natural language understanding
H. Weld, X. Huang, S. Long, J. Poon, and S. C. Han. 2021 · 2021
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Out-of-scope intent detection with self-supervision and discriminative training
Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, and Albert Y.S. Lam. 2021 · 2021
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Towards a unified view of parameter-efficient transfer learning
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Shahnawaz Khan and Mustafa Raza Rabbani. 2020 · 2020
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Simulating the effects of social presence on trust, privacy concerns & usage intentions in automated bots for finance
Magdalene Ng, Kovila P.L. Coopamootoo, Ehsan Toreini, Mhairi Aitken, Karen Elliot, and Aad van Moorsel. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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On the effectiveness of adapter-based tuning for pretrained language model adaptation
Ruidan He, Linlin Liu, Hai Ye, Qingyu Tan, Bosheng Ding, Liying Cheng, Jia-Wei Low, Lidong Bing, and Luo Si. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017a
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017b
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Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, and Graham Neubig. 2022 · 2022
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Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Jones, Tengyu Ma, and Percy Liang. 2022 · 2022
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P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks
Xiao Liu, Kaixuan Ji, Yicheng Fu, Weng Tam, Zhengxiao Du, Zhilin Yang, and Jie Tang. 2022 · 2022
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Learning discriminative representations and decision boundaries for open intent detection
Hanlei Zhang, Hua Xu, Shaojie Zhao, and Qianrui Zhou. 2022 · 2022
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A stack-propagation framework with token-level intent detection for spoken language understanding
Libo Qin, Wanxiang Che, Yangming Li, Haoyang Wen, and Ting Liu. 2019 · 2087
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