CIS 620 - Learning in Few-Labels Settings

The list will be updated constantly throughout the semester. Papers are sorted by year instead of any particular importance.

Ming-Wei Chang, Lev Ratinov, Dan Roth and Vivek Srikumar Importance of Semantic Representation: Dataless Classification 2008
Hugo Larochelle, Dumitru Erhan and Yoshua Bengio Zero-data Learning of New Tasks 2008
Christoph H. Lampert, Hannes Nickisch and Stefan Harmeling Learning to detect unseen object classes by between-class attribute transfer 2009
Bernardino Romera-Paredes and Philip Torr An embarrassingly simple approach to zero-shot learning 2015
Omer Levy, Minjoon Seo, Eunsol Choi and Luke Zettlemoyer Zero-Shot Relation Extraction via Reading Comprehension 2017
Ben Zhou, Daniel Khashabi, Chen-Tse Tsai and Dan Roth Zero-Shot Open Entity Typing as Type-Compatible Grounding 2018
Shashank Srivastava, Igor Labutov, Tom Mitchell Zero-shot Learning of Classifiers from Natural Language Quantification 2018
Wenpeng Yin, Jamaal Hay, Dan Roth Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach 2019
Yangqiu Song, Shyam Upadhyay, Haoruo Peng, Stephen Mayhew, Dan Roth Toward any-language zero-shot topic classification of textual documents 2019
Zhiquan Ye, Yuxia Geng, Jiaoyan Chen, Jingmin Chen, Xiaoxiao Xu, SuHang Zheng, Feng Wang, Jun Zhang, Huajun Chen Zero-shot Text Classification via Reinforced Self-training 2020
Colin Lockard, Prashant Shiralkar, Xin Luna Dong, Hannaneh Hajishirzi ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages 2020

Li Fei-Fei, Rob Fergus and Pietro Perona One-Shot learning of object categories 2006
Chelsea Finn, Pieter Abbeel and Sergey Levine Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks 2017
Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin, Pedro O. Pinheiro Adaptive Cross-Modal Few-shot Learning 2019
Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian, Jian Sun Induction Networks for Few-Shot Text Classification 2019
Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom and Zsolt Kira Multi-class Classification without Multi-class Labels 2019
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, Jia-Bin Huang A Closer Look at Few-shot Classification 2019
Yujia Bao, Menghua Wu, Shiyu Chang , Regina Barzilay Few-Shot Text Classification with Distributional Signatures 2020
Guneet Singh Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto A Baseline for Few-Shot Image Classification 2020
Yi Yang, Arzoo Katiyar Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning 2020

Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafsky Distant supervision for relation extraction without labeled data 2009
Maria-Florina Balcan and Avrim Blum A discriminative model for semi-supervised learning 2010
Timothee Cour, Ben Sapp and Ben Taskar Learning from Partial Labels 2011
Percy Liang, Michael I. Jordan and Dan Klein Learning Dependency-Based Compositional Semantics 2011
Liping Liu, Thomas Dietterich Learnability of the Superset Label Learning Problem 2014
Xiao Zhang, Dan Goldwasser Sentiment Tagging with Partial Labels using Modular Architectures 2019
Bo Shao , Yeyun Gong , Junwei Bao , Jianshu Ji3 , Guihong Cao , Xiaola Lin Duan Weakly Supervised Multi-task Learning for Semantic Parsing 2019
Qiang Ning and Hangfeng He and Chuchu Fan and Dan Roth Partial or Complete, That's The Question 2019
Ekin D. Cubuk, Barret Zoph , Dandelion Mane, Vijay Vasudevan, Quoc V. Le, AutoAugment: Learning Augmentation Strategies from Data 2019
Yuki M. Asano Christian Rupprecht Andrea Vedaldi A critical analysis of self-supervision, or what we can learn from a single image 2020
Bosheng Ding, Linlin Liu, Lidong Bing, Canasai Kruengkrai, Thien Hai Nguyen, Shafiq Joty, Luo Si, Chunyan Miao DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks 2020