About me

I am a Senior Applied Scientist from Amazon Search - Rufus, working on LLM for shopping. Previously, I worked in search Query Understanding (QU) team. 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]

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

  • Natural Language Processing: large language models (LLMs) & multi-modality (vision foundation model), instruction following/tuning, Knowledge graph, information extraction, question answering, sentiment analysis.
  • Machine Learning: transfer Learning, meta-learning, semi/weakly-supervised learning, multi-task learning, graph embedding.


  • May 2024 - Two papers were accepted by ICML 2024.
  • May 2024 - One paper was accepted by KDD 2024.
  • May 2024 - One paper was accepted by ACL 2024.
  • April 2024 - One paper was accepted by NAACL 2024.
  • March 2024 - We are hosting the 🛍️Amazon KDD Cup 2024: Multi-Task Online Shopping Challenge for LLMs with plenty of awards. Click here to contribute ingenious solutions 🚀!
  • Jan 2024 - One paper was accepted by SIGMOD 2024.
  • Jan 2024 - One paper was accepted by WWW 2024.
  • Dec 2023 - One survey paper about LLMs in Medicine was in Arkiv now.
  • Oct 2023 - Two papers were accepted by EMNLP 2023.
  • Sep 2023 - Two papers were accepted by NeurIPS 2023, one for our KDD Cup’23 benchmark dataset paper, and one for session-based recommendation.
  • June 2023 - Our paper “SCOTT“ has been selected for ACL 2023 Outstanding Paper Award
  • June 2023 - Invited to serve as Senoir Program Committee (SPC) for AAAI 2024.
  • May 2023 - One paper was accepted by KDD 2023.
  • Jan 2023 - Four papers were accepted by ACL 2023.
  • We have launched the Amazon KDD Cup’23 Competition, featuring a multilingual recommendation challenge. Feel free to submit your solutions and potentially win thousands of dollars!
  • Jan 2023 - One paper was accepted by WWW 2023.
  • Jan 2023 - One paper was accepted by ICLR 2023.


  • 2020-Present, Amazon Search (A9), Senior Applied Scientist, 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, + denotes interns/students i mentored)

  • A Survey of Large Language Models in Medicine: Progress, Application, and Challenge [pdf][github]
          Hongjian Zhou, Fenglin Liu+, Boyang Gu, Xinyu Zou, Jinfa Huang, Jinge Wu, Yiru Li, Sam S. Chen, Peilin Zhou, Junling Liu, Yining Hua, Chengfeng Mao, Chenyu You, Xian Wu, Yefeng Zheng, Lei Clifton, Zheng Li#, Jiebo Luo, David A. Clifton (Arkiv, 2024)

  • COSMO: A Large-Scale E-commerce Common Sense Knowledge Generation and Serving System at Amazon [pdf]
          Changlong Yu*+, Xin Liu*+, Jefferson Maia, Tianyu Cao, Yang Li, Yifan Gao, Yangqiu Song, Rahul Goutam, Haiyang Zhang, Bing Yin, Zheng Li*# (SIGMOD 2024)

  • Language Models As Semantic Indexers [pdf]
           Bowen Jin+, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang (ICML 2024)

  • MEMORYLLM: Toward Self-Updating Large Language Models [pdf]
           Yu Wang+, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian McAuley (ICML 2024)

  • Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs [pdf]
           Bowen Jin+, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han (ACL 2024)

  • IterAlign: Iterative Constitutional Alignment of Large Language Models [pdf]
           Xiusi Chen, Hongzhi Wen, Sreyashi Nag, Chen Luo, Qingyu Yin, Ruirui Li, Zheng Li, Wei Wang (NAACL 2024)

  • Understanding Inter-Session Intentions via Complex Logical Reasoning [pdf]
           Jiaxin Bai+, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song (KDD 2024)

  • Hierarchical Query Classification in E-commerce Search [pdf]
          Bing He+, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang (WWW 2024)

  • Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation [pdf][KDD Cup website]
          Wei Jin+, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang (NeurIPS 2023, our KDD Cup’23 benchmark paper)

  • Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns [pdf][code]
          Xin Liu+, Zheng Li#, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song (NeurIPS 2023)

  • Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning [pdf][code]
          Ruijie Wang+, Zheng Li#, Jingfeng Yang, Tianyu Cao, Bing Yin, Tarek Abdelzaher (WWW 2023)

  • SCOTT: Self-Consistent Chain-of-Thought Distillation [pdf][code]
          Peifeng Wang+, Zhengyang Wang, Zheng Li#, Yifan Gao, Bing Yin, Xiang Ren (ACL 2023, Outstanding Paper Award)

  • Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels [pdf][code]
          Fenglin Liu+, Bang Yang, Zheng Li#, Qingyu Yin, Chenyu You, Xuewei Ma, Bing Yin and Yuexian Zou (ACL 2023)

  • FolkScope: Intention Knowledge Graph Construction for E-commerce Commonsense Discovery [pdf][code]
          Changlong Yu+, Weiqi Zhang, Xin Liu+, Jiaxin Bai+, Yangqiu Song, Zheng Li, Yifan Gao, Tianyu Cao, Bing Yin, (ACL 2023)

  • Graph Reasoning for Question Answering with Triplet Retrieval pdf
          Shiyang Li+, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang and Bing Yin (ACL 2023)

  • Improving Consistency for Text Summarization with Energy Functions [pdf][code]
           Qi Zeng, Qingyu Yin, Zheng Li, Yifan Gao, Sreyashi Nag, Zhengyang Wang, Bing Yin, Heng Ji, Chao Zhang(EMNLP 2023)

  • Knowledge-Selective Pretraining for Attribute Value Extraction [pdf][code]
           Hui Liu, Qingyu Yin, Zhengyang Wang, Chenwei Zhang, Haoming Jiang, Yifan Gao, Zheng Li, Xian Li, Chao Zhang, Bing Yin, William Yang Wang, Xiaodan Zhu (EMNLP 2023)

  • Knowledge graph reasoning over entities and numerical values [pdf][code]
           Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song (KDD 2023)

  • HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers [pdf][code]
          Chen Liang+, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao (ICLR 2023)

  • Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graph [pdf][code]
          Ruijie Wang+, Zheng Li#, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher (NeurIPS 2022)

  • Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment [pdf][code][data][media]
          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]
          Ruijie Wang+, Zheng Li#, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin and Tarek Abdelzaher (WWW 2022, Long paper, Research track)

  • Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering [pdf]
          Juan Zha*, Zheng Li*, Ying Wei and Yu Zhang (EMNLP 2022, Long paper)

  • Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training [pdf][code][academic data][e-commerce data]
          Yifan Gao+, Qingyu Yin#, Zheng Li#, Rui Meng, Tong Zhao, Bing Yin, Irwin King, Michael Lyu (NAACL 2022, Long paper)

  • Condensing Graphs via One-Step Gradient Matching [pdf][code]
          Wei Jin+, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Yin (KDD 2022, Long paper, Research Track)

  • Query Attribute Recommendation at Amazon Search [pdf]
          Chen Luo, William Headean, Neela Avudaiappan, Haoming Jiang, Tianyu Cao, Qingyu Yin, Yifan Gao, Zheng Li, Rahul Goutam, Haiyang Zhang, Bing Yin (RecSys 2022, Industry Track)

  • Meta Teacher Student Network for Multilingual Sequence Labeling with Minimal Supervision [pdf][code]
          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, 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
          Wen-Kai Huan, Chang-Dong Wang, Shao-Shu Huan, Zheng Li, Jian-Huang Lai, Ling Huang, (IJSSE journal 2015)



  • Ruijie Wang, UIUC Ph.D. student, topic: Temporal Event Forecasting. Achievement: NeurIPS 2022, WWW 2022, WWW 2023.
  • Zijie Huang, UCLA Ph.D. student, topic: Multilingual KG completion. Achievement: ACL 2022.
  • Yifan Gao, CUHK Ph.D, topic: Multilingual Keyphrase Generation. Achievement: NAACL 2022 Finding. Now: Applied Scientist, Amazon.
  • Wei Jin, Michigan State University Ph.D, topic: Data Condensation. Achievement: KDD 2022, NeurIPS 2023, KDD Cup 2023. Now: Assistant Prof, Emory University.
  • Peifeng Wang, USC, Ph.D. Achievement: ACL 2023. ACL Outstanding Paper Award. Now: Research Scientist, Salesforce.
  • Yilun Jin, Hong Kong University of Science and Technology Ph.D, topic: LLM in Shopping. Achievement: KDD Cup 2024.
  • Chen Liang, Gatech Ph.D. student, topic: Knowledge Distillation. Achievement: ICLR 2023.
  • Changlong Yu, HKUST, Ph.D. Achievement: SIGMOD 2024, ACL 2023. Now: Applied Scientist, Amazon.
  • Fenglin Liu, Oxford, Ph.D. student. Achievement: ACL 2023.
  • Shiyang Li, UCSB, Ph.D. Achievement: ACL 2023. Now: Applied Scientist, Amazon.
  • Yujia Xie, Gatech Ph.D. student, topic: Extreme Multi-label Classification. Now: Senior Researcher, Microsoft.
  • Xin Liu, HKUST, Ph.D. Achievement: NeurIPS 2023. Now: Applied Scientist, Amazon.
  • Bing He, Gatech Ph.D. Achievement: WWWW 2024.
  • Jiaxin Bai, HKUST, Ph.D. student. Achievement: KDD 2023.
  • Qi Zeng, UIUC, Ph.D. student. Achievement: ACL 2023. Now: Research Scientist, Tiktok.
  • Hui Liu, Queen’s University, Ph.D. Achievement: ACL 2023. Now: Applied Scientist, Amazon.
  • Xiusu Chen, UCLA Ph.D. student.
  • Kewei Cheng, UCLA Ph.D. student.
  • Yu Wang, UCSD Ph.D. student.
  • Jie Huang, UIUC, Ph.D. student.
  • Enyan Dai, Penn State University, Ph.D.
  • Xutan Peng, University of Sheffield, Ph.D, topic: Multilingual KG pretraining.

Professional Activities

  • Program Organzier/Chair: KDD Cup 2023, 2024.
  • Senior Program Committee/Area Chair (Meta-Reviewer): AAAI (2024), AAAI (2023), IJCAI (2021)
  • Program Committee (Reviewer):
    • ACL, EMNLP, ICLR, AAAI, IJCAI (2020)
  • Conference Secondary Reviewer: AAAI, IJCAI (2019)
  • Journal Reviewer: PAMI, TBD, Neurocomputing

Honors & Awards

  • Jul 2023, ACL 2023 Outstanding Paper Award
  • 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