We summarize related research papers and resources for ontology expansion (OnExp). We categorize OnExp into New Intent Discovery (NID), New Slot-Value Discovery (NSVD), and Joint OnExp, as illustrated in the following figure:
We present a summary of the datasets widely used in OnExp tasks, as shown in the Table below.
- Understanding user goals in web search. Daniel E. Rose and Danny Levinson. WWW, 2004. [Paper]
- Determining the informational, navigational, and transactional intent of web queries. Bernard J. Jansen, Danielle L. Booth, and Amanda Spink. Inf, Process, Manag, 2008. [Paper]
- Some methods for classification and analysis of multivariate observations. James MacQueen. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 1976. [Paper]
- Agglomerative clustering using the concept of mutual nearest neighbourhood. K. Chidananda Gowda and G. Krishna. Pattern Recognit, 1978 [Paper]
- Behavior-driven clustering of queries into topics. Luca Maria Aiello, Debora Donato, Umut Ozertem, Filippo Menczer. CIKM, 2011. [Paper]
- Sequence clustering and labeling for unsupervised query intent discovery. Jackie Chi Kit Cheung, Xiao Li. WSDM, 2012. [Paper]
- Heterogeneous graph-based intent learning with queries, web pages and wikipedia concepts. Xiang Ren, Yujing Wang, Xiao Yu, Jun Yan, Zheng Chen, Jiawei Han. WSDM, 2014. [Paper]
- A weakly-supervised approach for discovering new user intents from search query logs. Dilek Hakkani-Tür, Asli Celikyilmaz, Larry P. Heck, Gökhan Tür. INTERSPEECH, 2013. [Paper]
- Clustering novel intents in a conversational interaction system with semantic parsing. Dilek Hakkani-Tür, Yun-Cheng Ju, Geoffrey Zweig, Gökhan Tür. INTERSPEECH, 2015. [Paper]
- Unsupervised deep embedding for clustering analysis. Junyuan Xie, Ross B. Girshick, Ali Farhadi. ICML, 2016. [Paper]
- Leveraging knowledge bases in lstms for improving machine reading. Bishan Yang, Tom M. Mitchell. ACL, 2017 [Paper]
- Deep adaptive image clustering. Jianlong Chang, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, Chunhong Pan. ICCV, 2017. [Paper]
- Deep clustering for unsupervised learning of visual features. Mathilde Caron, Piotr Bojanowski, Armand Joulin, Matthijs Douze. ECCV, 2018. [Paper]
- Supporting clustering with contrastive learning. Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen R. McKeown, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang. NAACL, 2021. [Paper]
- IDAS: Intent discovery with abstractive summarization. Maarten De Raedt, Fréderic Godin, Thomas Demeester, Chris Develder. NLP4ConvAI, 2023. [Paper]
- Zero-shot user intent detection via capsule neural networks. Congying Xia, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu. EMNLP, 2018. [Paper]
- Reconstructing capsule networks for zero-shot intent classification. Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu. EMNLP/IJCNLP, 2019. [Paper]
- Unknown intent detection using Gaussian mixture model with an application to zero-shot intent classification. Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam. ACL, 2020. [Paper]
- Generalized zero-shot intent detection via commonsense knowledge. A. B. Siddique, Fuad T. Jamour, Luxun Xu, Vagelis Hristidis. SIGIR, 2021. [Paper]
- Learning class-transductive intent representations for zero-shot intent detection. Qingyi Si, Yuanxin Liu, Peng Fu, Zheng Lin, Jiangnan Li, Weiping Wang. IJCAI, 2021. [Paper]
- A Label-Aware BERT Attention Network for Zero-Shot Multi-Intent Detection in Spoken Language Understanding. Ting-Wei Wu, Ruolin Su, Biing-Hwang Juang. EMNLP, 2021. [Paper]
- Template-based Approach to Zero-shot Intent Recognition. Dmitry Lamanov, Pavel Burnyshev, Ekaterina Artemova, Valentin Malykh, Andrey Bout, Irina Piontkovskaya. INLG, 2022. [Paper]
- A simple meta-learning paradigm for zero-shot intent classification with mixture attention mechanism. Han Liu, Siyang Zhao, Xiaotong Zhang, Feng Zhang, Junjie Sun, Hong Yu, Xianchao Zhang. SIGIR, 2022. [Paper]
- Pre-training intent-aware encoders for zero-and few-shot intent classification. Mujeen Sung, James Gung, Elman Mansimov, Nikolaos Pappas, Raphael Shu, Salvatore Romeo, Yi Zhang, Vittorio Castelli. EMNLP, 2023. [Paper]
- Exploring zero and few-shot techniques for intent classification. Soham Parikh, Mitul Tiwari, Prashil Tumbade, Quaizar Vohra. ACL Industry, 2023. [Paper]
- Active semi-supervision for pairwise constrained clustering. Sugato Basu, Arindam Banerjee, Raymond J. Mooney. SDM, 2004. [Paper]
- Learning to cluster in order to transfer across domains and tasks. Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira. ICLR, 2018 [Paper]
- Multi-class classification without multi-class labels. Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, Zsolt Kira. ICLR, 2019. [Paper]
- Discovering new intents via constrained deep adaptive clustering with cluster refinement. Ting-En Lin, Hua Xu, Hanlei Zhang. AAAI, 2020. [Paper]
- Learning to discover novel visual categories via deep transfer clustering. Kai Han, Andrea Vedaldi, Andrew Zisserman. ICCV, 2019. [Paper]
- Discovering new intents with deep aligned clustering. Hanlei Zhang, Hua Xu, Ting-En Lin, Rui Lyu. AAAI, 2021. [Paper]
- A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery. Hanlei Zhang, Huanlin Xu, Xin Wang, Fei Long, Kai Gao. TKDE, 2023. [Paper]
- A Probabilistic Framework for Discovering New Intents. Yunhua Zhou, Guofeng Quan, Xipeng Qiu. ACL, 2023. [Paper]
- Semi-supervised intent discovery with contrastive learning. Xiang Shen, Yinge Sun, Yao Zhang, Mani Najmabadi. NLP4CONVAI, 2021. [Paper]
- Intent detection and discovery from user logs via deep semi-supervised contrastive clustering. Rajat Kumar, Mayur Patidar, Vaibhav Varshney, Lovekesh Vig, Gautam Shroff. NAACL, 2021. [Paper]
- Generalized category discovery. Sagar Vaze, Kai Han† Andrea Vedaldi, Andrew Zisserman. CVPR, 2022. [Paper]
- Watch the neighbors: A unified k-nearest neighbor contrastive learning framework for OOD intent discovery. Yutao Mou, Keqing He, Pei Wang, Yanan Wu, Jingang Wang, Wei Wu, Weiran Xu. EMNLP, 2022. [Paper]
- Disentangled knowledge transfer for OOD intent discovery with unified contrastive learning. Yutao Mou, Keqing He, Yanan Wu, Zhiyuan Zeng, Hong Xu, Huixing Jiang, Wei Wu, Weiran Xu. ACL, 2022. [Paper]
- New intent discovery with pre-training and contrastive learning. Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam. ACL, 2022. [Paper]
- Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery. Yutao Mou, Xiaoshuai Song, Keqing He, Chen Zeng, Pei Wang, Jingang Wang, Yunsen Xian, Weiran Xu. ACL, 2023. [Paper]
- Generalized category discovery with decoupled prototypical network. Wenbin An, Feng Tian, Qinghua Zheng, Wei Ding, Qianying Wang, Ping Chen. AAAI, 2023. [Paper]
- Transfer and alignment network for generalized category discovery. Wenbin An, Feng Tian, Wenkai Shi, Yan Chen, Yaqiang Wu, Qianying Wang, Ping Chen. AAAI, 2024. [Paper]
- New Intent Discovery with Attracting and Dispersing Prototype. Shun Zhang, Jian Yang, Jiaqi Bai, Chaoran Yan, Tongliang Li, Zhao Yan, Zhoujun Li. LREC/COLING, 2024. [Paper]
- ClusterPrompt: Cluster semantic enhanced prompt learning for new intent discovery. Jinggui Liang, Lizi Liao. EMNLP Findings, 2023. [Paper]
- A diffusion weighted graph framework for new intent discovery. Wenkai Shi, Wenbin An, Feng Tian, Qinghua Zheng, Qianying Wang, Ping Chen. EMNLP, 2023. [Paper]
- Fine-grained category discovery under coarse-grained supervision with hierarchical weighted self-contrastive learning. Wenbin An, Feng Tian, Ping Chen, Siliang Tang, Qinghua Zheng, Qianying Wang. EMNLP, 2022. [Paper]
- DNA: Denoised neighborhood aggregation for fine-grained category discovery. Wenbin An, Feng Tian, Wenkai Shi, Yan Chen, Qinghua Zheng, Qianying Wang, Ping Chen. EMNLP, 2023. [Paper]
- Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection. Pei Wang, Keqing He, Yejie Wang, Xiaoshuai Song, Yutao Mou, Jingang Wang, Yunsen Xian, Xunliang Cai, Weiran Xu. LREC/COLING, 2024. [Paper]
- Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPT. Xiaoshuai Song, Keqing He, Pei Wang, Guanting Dong, Yutao Mou, Jingang Wang, Yunsen Xian, Xunliang Cai, Weiran Xu. EMNLP, 2023. [Paper]
- Clusterllm: Large language models as a guide for text clustering. Yuwei Zhang, Zihan Wang, Jingbo Shang. EMNLP, 2023. [Paper]
- Large language models enable few-shot clustering. ijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Graham Neubig. [Paper]
- Generalized Category Discovery with Large Language Models in the Loop. Wenbin An, Wenkai Shi, Feng Tian, Haonan Lin, Qianying Wang, Yaqiang Wu, Mingxiang Cai, Luyan Wang, Yan Chen, Haiping Zhu, Ping Chen. [Paper]
- Actively Learn from LLMs with Uncertainty Propagation for Generalized Category Discovery. Jinggui Liang, Lizi Liao, Hao Fei, Bobo Li, Jing Jiang. NAACL, 2024. [Paper]
- Leveraging frame semantics and distributional semantics for unsupervised semantic slot induction in spoken dialogue systems. Yun-Nung Chen, William Yang Wang, Alexander I. Rudnicky. SLT, 2014. [Paper]
- Jointly modeling inter-slot relations by random walk on knowledge graphs for unsupervised spoken language understanding. Yun-Nung Chen, William Yang Wang, Alexander I. Rudnicky. NAACL, 2015. [Paper]
- Discovering Dialogue Slots with Weak Supervision. Vojtech Hudecek, Ondrej Dusek, Zhou Yu. ACL/IJCNLP, 2021. [Paper]
- Unsupervised slot schema induction for task-oriented dialog. Dian Yu, Mingqiu Wang, Yuan Cao, Izhak Shafran, Laurent El Shafey, Hagen Soltau. NAACL, 2022. [Paper]
- Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive Learning. Hoang H. Nguyen, Chenwei Zhang, Ye Liu, Philip S. Yu. SIGDIAL, 2023. [Paper]
- Towards unsupervised spoken language understanding: Exploiting query click logs for slot filling. Gökhan Tür, Dilek Hakkani-Tür, Dustin Hillard, Asli Celikyilmaz. INTERSPEECH, 2011. [Paper]
- Unsupervised person slot filling based on graph mining. Dian Yu, Heng Ji. ACL, 2016. [Paper]
- Unsupervised Slot Filler Refinement via Entity Community Construction. Zengzhuang Xu, Rui Song, Bowei Zou, Yu Hong. NLPCC, 2017. [Paper]
- Combining Word-Level and Character-Level Representations for Relation Classification of Informal Text. Dongyun Liang, Weiran Xu, Yinge Zhao. Rep4NLP@ACL, 2017. [Paper]
- A novel unsupervised approach for precise temporal slot filling from incomplete and noisy temporal contexts. Xueying Wang, Haiqiao Zhang, Qi Li, Yiyu Shi, Meng Jiang. WWW, 2019. [Paper]
- Improving slot filling in spoken language understanding with joint pointer and attention. Lin Zhao, Zhe Feng. ACL, 2018. [Paper]
- Few-shot representation learning for out-of-vocabulary words. Ziniu Hu, Ting Chen, Kai-Wei Chang, Yizhou Sun. ACL, 2019. [Paper]
- Learning to tag OOV tokens by integrating contextual representation and background knowledge. Keqing He, Yuanmeng Yan, Weiran Xu. ACL, 2020. [Paper]
- Span-ConveRT: Few-shot span extraction for dialog with pretrained conversational representations. Sam Coope, Tyler Farghly, Daniela Gerz, Ivan Vulic, Matthew Henderson. ACL, 2020. [Paper]
- Transfer learning for sequence labeling using source model and target data. Lingzhen Chen, Alessandro Moschitti. AAAI, 2019. [Paper]
- Learning label-relational output structure for adaptive sequence labeling. Keqing He, Yuanmeng Yan, Hong Xu, Sihong Liu, Zijun Liu, Weiran Xu. IJCNN, 2020. [Paper]
- Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network. Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, Ting Liu. ACL, 2020. [Paper]
- Few-shot learning for slot tagging with attentive relational network. Cennet Oguz, Ngoc Thang Vu. EACL, 2021. [Paper]
- HierarchicalContrast: A Coarse-to-Fine Contrastive Learning Framework for Cross-Domain Zero-Shot Slot Filling. Junwen Zhang, Yin Zhang. EMNLP Findings, 2023. [Paper]
- Bridge to target domain by prototypical contrastive learning and label confusion: Re-explore zero-shot learning for slot filling. Liwen Wang, Xuefeng Li, Jiachi Liu, Keqing He, Yuanmeng Yan, Weiran Xu. EMNLP, 2021. [Paper]
- Generative zero-shot prompt learning for cross-domain slot filling with inverse prompting. Xuefeng Li, Liwen Wang, Guanting Dong, Keqing He, Jinzheng Zhao, Hao Lei, Jiachi Liu, Weiran Xu. ACL Findings, 2023. [Paper]
- Towards zero-shot frame semantic parsing for domain scaling. Ankur Bapna, Gökhan Tür, Dilek Hakkani-Tür, Larry P. Heck. INTERSPEECH, 2017. [Paper]
- Robust zero-shot cross-domain slot filling with example values. Darsh J. Shah, Raghav Gupta, Amir A. Fayazi, Dilek Hakkani-Tür. ACL, 2019. [Paper]
- Zero-shot adaptive transfer for conversational language understanding. Sungjin Lee, Rahul Jha. AAAI, 2019. [Paper]
- Coach: A coarse-to-fine approach for cross-domain slot filling. Zihan Liu, Genta Indra Winata, Peng Xu, Pascale Fung. ACL, 2020. [Paper]
- Contrastive zero-shot learning for cross-domain slot filling with adversarial attack. Keqing He, Jinchao Zhang, Yuanmeng Yan, Weiran Xu, Cheng Niu, Jie Zhou. COLING, 2020. [Paper]
- QA-driven zero-shot slot filling with weak supervision pretraining. Xinya Du, Luheng He, Qi Li, Dian Yu, Panupong Pasupat, Yuan Zhang. ACL/IJCNLP, 2021. [Paper]
- Cross-domain slot filling as machine reading comprehension: A new perspective. Jian Liu, Mengshi Yu, Yufeng Chen, Jinan Xu. IEEE ACM Trans. Audio Speech Lang. Process, 2022. [Paper]
- Zero-shot slot filling with slot-prefix prompting and attention relationship descriptor. Qiaoyang Luo, Lingqiao Liu. AAAI, 2023. [Paper]
- Semi-supervised new slot discovery with incremental clustering. Yuxia Wu, Lizi Liao, Xueming Qian, Tat-Seng Chua. EMNLP Findings, 2022. [Paper]
- Active discovering new slots for task-oriented conversation. Yuxia Wu, Tianhao Dai, Zhedong Zheng, Lizi Liao. IEEE ACM Trans. Audio Speech Lang. Process, 2024. [Paper]
- Automatic intent-slot induction for dialogue systems. Zengfeng Zeng, Dan Ma, Haiqin Yang, Zhen Gou, Jianping Shen. WWW, 2021. [Paper]
Efficient Intent Detection with Dual Sentence Encoders. Iñigo Casanueva, Tadas Temcinas, Daniela Gerz, Matthew Henderson, Ivan Vulic. NLP4ConvAI, 2020. [Paper] [Code] [Data]
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, Jason Mars. EMNLP/IJCNLP, 2019. [Paper] [Code] [Data]
Short Text Clustering via Convolutional Neural Networks. Jiaming Xu, Peng Wang, Guanhua Tian, Bo Xu, Jun Zhao, Fangyuan Wang, Hongwei Hao. VS@HLT-NAACL, 2015. [Paper] [Code] [Data]
A network-based end-to-end trainable task-oriented dialogue system. Tsung-Hsien Wen, David Vandyke, Nikola Mrksic, Milica Gasic, Lina Maria Rojas-Barahona, Pei-Hao Su, Stefan Ultes, Steve J. Young. EACL, 2017. [Paper] [Code] [Data]
Discriminative spoken language understanding using word confusion networks. Matthew Henderson, Milica Gasic, Blaise Thomson, Pirros Tsiakoulis, Kai Yu, Steve J. Young. SLT, 2012. [Paper] [Data]
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines. Mihail Eric, Rahul Goel, Shachi Paul, Abhishek Sethi, Sanchit Agarwal, Shuyang Gao, Adarsh Kumar, Anuj Goyal, Peter Ku, Dilek Hakkani-Tur. LREC, 2020. [Paper] [Code] [Data]
The ATIS spoken language systems pilot corpus. Charles T. Hemphill, John J. Godfrey, George R. Doddington. HLT, 1990. [Paper] [Data]
Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces. Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, Maël Primet, Joseph Dureau. 2018. [Paper] [Code] [Data]
Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue Dataset. Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, Pranav Khaitan. AAAI, 2019. [Paper] [Code] [Data]