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The eXtreme Multi-label text Classification (XMC) problem concerns finding most relevant labels for an input text instance from a large label set.
Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Multiclass-multilabel classification with more classes than examples
Ofer Dekel and Ohad Shamir · 2010
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Mining of massive datasets
Anand Rajaraman and Jeffrey David Ullman · 2011
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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FastXML: A fast, accurate and stable tree-classifier for extreme multi-label learning
Yashoteja Prabhu and Manik Varma · 2014
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Asymmetric lsh (alsh) for sublinear time maximum inner product search (mips)
Anshumali Shrivastava and Ping Li · 2014
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Sparse local embeddings for extreme multi-label classification
Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, and Prateek Jain · 2015
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The extreme classification repository: Multi-label datasets and code, 2016
K. Bhatia, K. Dahiya, H. Jain, P. Kar, A. Mittal, Y. Prabhu, and M. Varma · 2016
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Quantization based fast inner product search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, and David Simcha · 2016
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Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs
Yu A Malkov and Dmitry A Yashunin · 2018
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Parabel: Partitioned label trees for extreme classification with application to dynamic search advertising
Yashoteja Prabhu, Anil Kag, Shrutendra Harsola, Rahul Agrawal, and Manik Varma · 2018
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Large-scale multi-label text classification on EU legislation
Ilias Chalkidis, Emmanouil Fergadiotis, Prodromos Malakasiotis, and Ion Androutsopoulos · 2019
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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
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Breaking the glass ceiling for embedding-based classifiers for large output spaces
Chuan Guo, Ali Mousavi, Xiang Wu, Dan Holtmann-Rice, Satyen Kale, Sashank Reddi, and Sanjiv Kumar · 2019
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Revisiting self-training for neural sequence generation
Junxian He, Jiatao Gu, Jiajun Shen, and Marc’Aurelio Ranzato · 2019
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Slice: Scalable linear extreme classifiers trained on 100 million labels for related searches
Himanshu Jain, Venkatesh Balasubramanian, Bhanu Chunduri, and Manik Varma · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova · 2019
Cited alongside, same era.
Extreme classification in log memory using count-min sketch: A case study of amazon search with 50m products
Tharun Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, and Anshumali Shrivastava · 2019
Cited alongside, same era.
Stochastic negative mining for learning with large output spaces
Sashank J Reddi, Satyen Kale, Felix Yu, Daniel Holtmann-Rice, Jiecao Chen, and Sanjiv Kumar · 2019
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych · 2019
Cited alongside, same era.
Billion-scale semi-supervised learning for image classification
I Zeki Yalniz, Hervé Jégou, Kan Chen, Manohar Paluri, and Dhruv Mahajan · 2019
Cited alongside, same era.
MPNet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu · 2020
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Self-training with noisy student improves imagenet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, and Quoc V Le · 2020
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PECOS: Prediction for enormous and correlated output spaces
Hsiang-Fu Yu, Kai Zhong, and Inderjit S Dhillon · 2020
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Rethinking pre-training and self-training
Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D Cubuk, and Quoc V Le · 2020
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Extreme multi-label learning for semantic matching in product search
Wei-Cheng Chang, Daniel Jiang, Hsiang-Fu Yu, Choon Hui Teo, Jiong Zhang, Kai Zhong, Kedarnath Kolluri, Qie Hu, Nikhil Shandilya, Vyacheslav Ievgrafov, et al · 2021
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AttentionXML: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification
Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, and Shanfeng Zhu · 2019
Cited alongside, same era.
Pre-training tasks for embedding-based large-scale retrieval
Wei-Cheng Chang, Felix X Yu, Yin-Wen Chang, Yiming Yang, and Sanjiv Kumar · 2020
Cited alongside, same era.
Taming pretrained transformers for extreme multi-label text classification
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, and Inderjit S Dhillon · 2020
Cited alongside, same era.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang · 2020
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Cited alongside, same era.
Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
Cited alongside, same era.
SiameseXML: Siamese networks meet extreme classifiers with 100m labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, K Gururaj, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, and Manik Varma · 2021
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DeepXML: A deep extreme multi-label learning framework applied to short text documents
Kunal Dahiya, Deepak Saini, Anshul Mittal, Ankush Shaw, Kushal Dave, Akshay Soni, Himanshu Jain, Sumeet Agarwal, and Manik Varma · 2021
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SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen · 2021
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Generalized zero-shot extreme multi-label learning
Nilesh Gupta, Sakina Bohra, Yashoteja Prabhu, Saurabh Purohit, and Manik Varma · 2021
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ECLARE: Extreme classification with label graph correlations
Anshul Mittal, Noveen Sachdeva, Sheshansh Agrawal, Sumeet Agarwal, Purushottam Kar, and Manik Varma · 2021
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Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych · 2021
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk · 2021
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Session-aware query auto-completion using extreme multi-label ranking
Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, and Inderjit S. Dhillon · 2021
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Fast multi-resolution transformer fine-tuning for extreme multi-label text classification
Jiong Zhang, Wei-cheng Chang, Hsiang-fu Yu, and Inderjit S Dhillon · 2021
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Contrastive pre-training for zero-shot information retrieval
Anonymous · 2022
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