Fetching the paper…
Reading the bibliography…
Intent discovery is the task of inferring latent intents from a set of unlabeled utterances, and is a useful step towards the efficient creation of new conversational agents.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
The hungarian method for the assignment problem
Harold W Kuhn. 1955 · 1955
Earlier work this paper cites.
A statistical interpretation of term specificity and its application in retrieval
Karen Sparck Jones. 1972 · 1972
Earlier work this paper cites.
Least squares quantization in pcm
Stuart Lloyd. 1982 · 1982
Earlier work this paper cites.
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Peter J Rousseeuw. 1987 · 1987
Earlier work this paper cites.
Wordnet: a lexical database for english
George A Miller. 1995 · 1995
Earlier work this paper cites.
A density-based algorithm for discovering clusters in large spatial databases with noise
Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu. 1996 · 1996
Earlier work this paper cites.
Mean shift: A robust approach toward feature space analysis
Dorin Comaniciu and Peter Meer. 2002 · 2002
Earlier work this paper cites.
Ontologies improve text document clustering
Andreas Hotho, Steffen Staab, and Gerd Stumme. 2003 · 2003
Earlier work this paper cites.
Properties of the hubert-arable adjusted rand index
Douglas Steinley. 2004 · 2004
Earlier work this paper cites.
Clustering short texts using wikipedia
Somnath Banerjee, Krishnan Ramanathan, and Ajay Gupta. 2007 · 2007
Earlier work this paper cites.
Clustering by passing messages between data points
Brendan J Frey and Delbert Dueck. 2007 · 2007
Earlier work this paper cites.
Exploiting wikipedia as external knowledge for document clustering
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, Eun K Park, and Xiaohua Zhou. 2009 · 2009
Earlier work this paper cites.
Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. 2011 · 2011
Cited alongside, same era.
Skip-thought vectors
Ryan Kiros, Yukun Zhu, Russ R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Cited alongside, same era.
A semantic approach for text clustering using wordnet and lexical chains
Tingting Wei, Yonghe Lu, Huiyou Chang, Qiang Zhou, and Xianyu Bao. 2015 · 2015
Cited alongside, same era.
Short text clustering via convolutional neural networks
Jiaming Xu, Peng Wang, Guanhua Tian, Bo Xu, Jun Zhao, Fangyuan Wang, and Hongwei Hao. 2015 · 2015
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Supporting clustering with contrastive learning
Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen McKeown, Ramesh Nallapati, Andrew O. Arnold, and Bing Xiang. 2021a · 2021
Later among the works it cites.
Effectiveness of pre-training for few-shot intent classification
Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, and Albert Y.S. Lam. 2021d · 2021
Later among the works it cites.
Meta-learning via language model in-context tuning
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, and He He. 2022 · 2022
Later among the works it cites.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022
Later among the works it cites.
What makes good in-context examples for GPT-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze. 2018b · 2018
Cited alongside, same era.
A self-training approach for short text clustering
Amir Hadifar, Lucas Sterckx, Thomas Demeester, and Chris Develder. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Efficient intent detection with dual sentence encoders
Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, Matthew Henderson, and Ivan Vulić. 2020 · 2020
Cited alongside, same era.
Discovering new intents via constrained deep adaptive clustering with cluster refinement
Ting-En Lin, Hua Xu, and Hanlei Zhang. 2020 · 2020
Cited alongside, same era.
SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
Cited alongside, same era.
Z-icl: Zero-shot in-context learning with pseudo-demonstrations
Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2022 · 2022
Later among the works it cites.
MetaICL: Learning to learn in context
Sewon Min, Mike Lewis, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2022b · 2022
Later among the works it cites.
Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022c · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Gray, et al. 2022 · 2022
Later among the works it cites.
Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2022 · 2022
Later among the works it cites.
An information-theoretic approach to prompt engineering without ground truth labels
Taylor Sorensen, Joshua Robinson, Christopher Rytting, Alexander Shaw, Kyle Rogers, Alexia Delorey, Mahmoud Khalil, Nancy Fulda, and David Wingate. 2022 · 2022
Later among the works it cites.
New intent discovery with pre-training and contrastive learning
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, and Albert Lam. 2022 · 2022
Later among the works it cites.