About me
I am an Applied Scientist from Amazon Search. I obtained my Ph.D. degree from the Department of Computer Science and Engineering, Hong Kong University of Science and Technology (HKUST). My supervisor is Prof. Qiang Yang. Before joining HKUST, I obtained the B.Eng degree from School of Data and Computer Science, Sun Yat-sen University (SYSU). [Github][Google Scholar][Resume (old)]
Research internship positions in Amazon Search (Base: Bay area) are available. Feel free to send your CV to me if you are interested.
Research interests
My current research is Low-Resource Natural Language Processing (LR-NLP), including cross-lingual/multilingual, cross-domain, and multi-task scenarios, etc. Revolving around this goal, I mainly study the following topics:
- Machine Learning: transfer Learning, meta-learning, semi/weakly-supervised learning, multi-task learning, graph embedding.
- Natural Language Processing: knowledge graph, information extraction, question answering, sentiment analysis.
Recently interesting topics: multilingual product knowledge graph, time-series graph mining, xmc: extreme multi-label classification, weakly-suprvised learning for NLP.
News
- Apr 2022 - One long paper was accepted by NAACL-Finding 2022.
- Feb 2022 - One long paper was accepted by ACL 2022.
- Jan 2022 - One long paper was accepted by WWW 2022.
- Jan 2022 - Invited to serve as Program Committee for ICML 2022.
- Jan 2022 - Invited to serve as Program Committee for IJCAI 2022.
- Nov 2021 - Invited to serve as Program Committee for KDD 2022.
- Nov 2021 - Invited to serve as Reviewer for ACL 2022 Rolling review.
- Aug 2021 - One long paper was accepted by EMNLP 2021.
- Jun 2021 - Invited to serve as Program Committee for AAAI 2022.
- Aug 2021 - One long paper was accepted by CIKM 2021 (Industry track).
- Jun 2021 - Invited to serve as Program Committee for ICLR 2022.
- April 2021 - Invited to serve as Program Committee for NeurIPS 2021.
- Mar 2021 - Invited to serve as Program Committee for EMNLP 2021.
Experiences
- Jan 2021-Present, Amazon Search (A9), Applied Scientist II, Bay Area, USA.
- Jun 2020-Sep 2020, Google Research, Research intern, NLX Group, Mountain View, CA, USA.
- Seq 2019-Dec 2019, Amazon Search (A9), Applied scientist intern, Search and NLP group, Palo, Alto, CA, USA. Research topic: Meta Learning, Cross-lingual transfer.
- Jun 2016-Aug 2016, HKUST Fok Ying Tung Research, Research intern, Mentor, Prof. Qiang Yang
- Jul 2015-Oct 2015, Microsoft Research Asia (MSRA), Research intern, Multimedia Search and Mining Group. Mentor: Dr. Tao Mei
Publications [Google Scholar]
(* denotes equal contributions, # denotes the corresponding author)
Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training [pdf][Code& Data coming soon]
Yifan Gao, Qingyu Yin#, Zheng Li#, Rui Meng, Tong Zhao, Bing Yin, Irwin King, Michael Lyu (NAACL-Finding 2022, Long paper)Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment [pdf][Code& Data coming soon]
Zijie Huang, Zheng Li#, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang (ACL 2022, Long paper)RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph [pdf][Code coming soon]
Ruijie Wang, Zheng Li#, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin and Tarek Abdelzaher (WWW 2022, Long paper, Research track)Meta Teacher Student Network for Multilingual Sequence Labeling with Minimal Supervision [pdf][code by request]
Zheng Li, Danqing Zhang, Tianyu Cao, Yiwei Song, Bing Yin (EMNLP 2021, Long paper, poster)
- QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction [pdf]
Danqing Zhang*, Zheng Li*, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang (CIKM 2021, Long paper, Applied science track.)
Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages [pdf]
Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang, Qiang Yang (EMNLP 2020, Long paper, oral)Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning [pdf][slides][code]
Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang (EMNLP 2019, Long paper, oral)
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification [pdf][slides][data]
Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li, Qiang Yang (AAAI 2019, oral)Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification [pdf][slides][code][demo]
Zheng Li, Ying Wei, Yu Zhang, Yuxiang Wu, Qiang Yang (AAAI 2018, oral)
End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification [pdf][slides][code]
Zheng Li, Yu Zhang, Ying Wei, Yuxiang Wu, Qiang Yang (IJCAI 2017, oral)Compressive Perceptual Hashing Tracking [pdf]
Zheng Li, Long Chen, Jian-Fei Yang, Neurocomputing 2017.Online Visual Tracking via Correlation Filter with Convolutional Networks [pdf][slides][demo]
Zheng Li, Jianfei Yang, Juan Zha, Chang-Dong Wang, Weishi Zheng (VCIP 2016, Oral).Compressive Perceptual Hashing Tracking with Online foreground learning [pdf][slides][demo]
Zheng Li, Jian-Fei Yang, Long Chen, Juan Zha (ROBIO 2015, Oral).Robust Vehicle Tracking Using Perceptual Hashing Algorithm [pdf]
Zheng Li, Jian-Fei Yang, Long Chen, Juan Zha (ICMLA 2015, Oral).Long-Term Revenue Maximization Pricing Scheme for Cloud [pdf]
Wen-Kai Huan, Chang-Dong Wang, Shao-Shu Huan, Zheng Li, Jian-Huang Lai, Ling Huang, (IJSSE journal 2015)
Projects
- Coffee Tag Cloud [demo][sample1][sample2][sample3]
- Domain Attention Transfer [demo]
- Cross-Granularity Aspect-based Sentiment Analysis [demo]
Mentership
- Yujia Xie, Gatech Ph.D. student, topic: Extreme Multi-label Classification
- Yifan Gao, CUHK Ph.D. student, topic: Multilingual Keyphrase Generation
- Ruijie Wang, UIUC Ph.D. student, topic: Temporal Event Forecasting
- Zijie Huang, UCLA Ph.D. student, topic: Multilingual KG completion
- Xutan Peng, University of Sheffield, Ph.D. student, topic: Multilingual KG pretraining
- Chen Liang, Gatech Ph.D. student, topic: Knowledge Distillation
- Wei Jin, Michigan State University Ph.D. student, topic: Data Condensation
Professional Activities
- Senior Program Committee: IJCAI (2021)
- Program Committee (Reviewer):
- ICLR, ICML, KDD, ACL, NAACL, AAAI, IJCAI (2022)
- NeurIPS, ICLR, ACL, EMNLP, NAACL, AAAI, IJCAI (2021)
- ACL, EMNLP, ICLR, AAAI, IJCAI (2020)
- Conference Secondary Reviewer: AAAI, IJCAI (2019)
- Journal Reviewer: PAMI, TBD, Neurocomputing
Honors & Awards
- Nov 2018, Baidu PhD Fellowship Nomination Awards, about 20/5,000 applicants worldwide.
- 2017-2019, AAAI19, AAAI18, IJCAI17 student travel awards
- Jun 2016, Excellent Graduates Awards, Sun Yat-sen University
- May 2016, Excellent Undergraduate Thesis Awards, Sun Yat-sen University
- Sep 2015, “YongSheng Liu” Excellent Undergraduate Scholarship
- Sep 2015, First-class Merit Scholarship, Sun Yat-sen University
- Aug 2015, “HUAWEI” Cup China Intelligent Design Competition, Second Prize
- Sep 2014, Second-class Merit Scholarship, Sun Yat-sen University
- Sep 2013, Third-class Merit Scholarship, Sun Yat-sen University