Ruirui Li

Staff Machine Learning Scientist&Engineer


Email: goldenbearray at gmail dot com


About Me

I am a staff machine learning scientist&enginneer at Coupang specializing in applied machine learning and deep learning, with a focus on pricing, product mapping and monitoring. Before that, I worked on search query understanding, query rewriting, related and trending searches, speaker verification/identification, and leveraging large language models (LLMs) for shopping and evaluation (LLM-as-a-Judge) at Amazon. I earned my Ph.D. from UCLA under the guidance of Prof. Wei Wang, my MPhil from The University of Hong Kong, where I worked with Prof. Ben Kao, and my B.S. from Nanjing University.

Experiences

  • 2025 - Now Staff Machine Learning Scientist&Engineer, Coupang
  • 2022 - 2025 Senior Applied Scientist, Amazon Search
  • 2019 - 2022 Applied Scientist, Amazon Alexa
  • 2013 - 2019 Research Assistant, University of California, Los Angeles

    • Publications

    2025

    1. Tianci Liu, Ruirui Li, Haoyu Wang, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Cheng, Jun Huan, Jing Gao, Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning, (ICLR'25), Singapore, 2025.

    2023&2024

    1. Haoyu Wang, Tianci Liu, Ruirui Li, Monica Cheng, Tuo Zhang, Jing Gao, RosaLora: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning, (EMNLP'24), Miami, 2024.
    2. Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao, Tuo Zhao, Jing Gao. BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering, (EMNLP'24), Miami, 2024.
    3. Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danni Zhang, Jasha Droppo, Monica Cheng, Ying Yin, Suhang Wang, Jing Gao, A Lightweight Representation Quantization Framework for Long-tail Data, (ICDE'24), Utrecht, Netherlands, 2024.
    4. Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang, Towards Universal Multi-Modal Personalization: A Language Model Empowered Generative Paradigm, (ICLR'24), Vienna, Austria, 2024.
    5. Xiusi Chen, Hongzhi Wen, Sreyashi Nag, Chen Luo, Qingyu Yin, Ruirui Li, Zheng Li, Wei Wang, IterAlign: Iterative Constitutional Alignment of Large Language Models, (NAACL'24), Mexico City, Mexico, 2024.
    6. Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang wang, Zheng Li, Yang Li, Hanqing Lu, Suhang wang, Jiawei Han, Xiafeng Tang, Language Models as Semantic Indexers, (ICML'24), Vienna, Austria, 2024.
    7. Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han, Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs, (ACL Findings), Bangkok, Thailand, 2024.
    8. Kewei Cheng, Jingfeng Yang, Zhengyang Wang, Binxuan Huang, Haoming Jiang, Ruirui Listrong>, Shiyang Li, Zheng Li, Yifan Gao, Xian Li, Bing Yin, Yizhou SunInductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs, LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models, (ACL'24), Bangkok, Thailand, 2024.
    9. 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, Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation, (NeurIPS'23), New Orleans, 2023.
    10. Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao, LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models, (KDD'23), Long Beach, 2023.

    2022&2021

    1. Metehan Cekic, Ruirui Li, Zeya Chen, Yuguang Yang, Andreas Stolcke, Upamanyu Madhow. Self-supervised Speaker Recognition Training Using Human-Machine Dialogues, (ICASSP'22), Singapore, 2022.
    2. Xin Zhang*, Minho Jin*, Roger Cheng, Ruirui Li, Eunjung Han, Andreas Stolcke. Contrastive-Mixup Learning for Improved Speaker Verification, (ICASSP'22), Singapore, 2022.
    3. Ruirui Li, Chelsea J.-T. Ju, Zeya Chen, Hongda Mao, Oguz Elibol, and Andreas Stolcke, Fusion of Embeddings Networks for Robust Combination of Text Dependent and Independent Speaker Recognition. (INTERSPEECH'21), Brno, Czechia, 2021.
    4. Haici Yang, Hongda Mao, Ruirui Li, Chelsea J.T. Ju, and Oguz Elibol, Non-local Convolutional Neural Networks (NLCNN) for Speaker Recognition. (INTERSPEECH'21), Brno, Czechia, 2021. [Submitted]
    5. Tianxin Wei*, Ruirui Li*, and Oguz Elibol, Adversarial Multi-task Learning for Speaker Recognition with Self-supervised Reconstructions. (INTERSPEECH'21), Brno, Czechia, 2021. [Submitted]
    6. Jie Pu, Yuguang Yang*, Ruirui Li*, and Oguz Elibol, Scaling Effect of Self-Supervised Speech Models. (INTERSPEECH'21), Brno, Czechia, 2021.

    2020&before

    1. Ruirui Li, Jyun-Yu Jiang, Chu-Cheng Hsieh, and Andreas Stolcke, Speaker Identification for Household Scenarios with Self-attention and Adversarial Training. (InterSpeech'20), Shanghai, China, 2020. [paper]
    2. Ruirui Li, Jyun-Yu Jiang,, Hongda Mao, Chu-Cheng Hsieh, and Wei Wang, Bridging Mixture Density Networks with Meta-learning for Automatic Speaker Identification. (ICASSP'20), Barcelona, Spain, 2020. [paper, video]
    3. Ruirui Li, Xiusi Chen, and Wei Wang, Few-shot Learning for New User Recommendation in Location-based Social Networks. (WWW'20), Taipei, Taiwan, 2020. [paper, video]
    4. Huaxiu Yao, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, and Zhenhui Li, Automated Relational Meta-learning. (ICLR'20), Addis Ababa, Ethiopia 2020. [paper]
    5. Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, and Wei Wang, Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning. (ICDM'20), Sorrento, Italy, 2020.
    6. Ruirui Li, and Wei Wang, Adversarial Learning to Compare: Self-Attentive Prospective Customer Recommendation in Location-baesd Social Networks. (WSDM'20), Houston, Texas, 2020. [paper]
    7. Ruirui Li, Jyun-Yu Jiang, Jiahao Liu, Chu-Cheng Hsieh, and Wei Wang, Automatic Speaker Recognition with Limited Data. (WSDM'20), Houston, Texas 2020. [paper]
    8. Ruirui Li, Liangda Li, Yunhong Zhou, and Wei Wang, Click Feedback-Aware Query Recommendation Using Adversarial Examples. (WWW'19), San Francisco, CA, 2019. [paper]
    9. Ruirui Li, Jyun-Yu Jiang, Chelsea J.-T. Ju, and Wei Wang, CORALS: Who are My Potential New Customers? Tapping into the Wisdom of Customers' Decisions. (WSDM'19), Melbourne, Australia, 2019. [paper]
    10. Ruirui Li, Jyun-Yu Jiang, Chelsea J.-T, Cheryl Flynn, Wen-ling Hsu, Jia Wang, Wei Wang, and Tan Xu, Enhancing Response Generation Using Chat Flow Identification. (KDD'18 Workshop), London, Aug. 2018.
    11. Zijun Xue, Mingda Li, and Ruirui Li, Recent Progress in Conversational AI. (KDD'18 Workshop), London, Aug. 2018.
    12. Chelsea J.-T. Ju, Ruirui Li, Zhengliang Wu, Jyun-Yu Jiang, Zhao Yang, and Wei Wang, Fleximer: Accurate Quatification of RNA-Seq via Variable-Length k-mers. (ACM BCB'17), Boston, 2017
    13. Ruirui Li, Xinxin Huang, Shuo Song, Jia Wang, and Wei Wang, Towards customer trouble tickets resolution automation in large cellular services. (Mobicom'16), New York, 2016.
    14. Liuli Chen, Jennifer Zhang, Chelsea J.-T. Ju, Ruirui Li, Wenchao Yu, and Wei Wang, Skimdiff: Transcript-level differential analysis of RNA-Seq data. (HitSeq'15), Dublin, Ireland. 2015.
    15. Ruirui Li, and Wei Wang, REAFUM: Representative Approximate Frequent Subgraph Mining. (SDM'15), Vancouver, Apr. 2015. [paper]
    16. Ruirui Li, Ben Kao, Bin Bi, Reynold Cheung, and Eric Lo, DQR: A probabilistic approach to diversified query recommendation. (CIKM'12), Hawaii, Oct. 2012. [paper]

    Selected Awards

    • WSDM Travel Grant, SIGIR, 2019, 2020.
    • Yahoo! FREP Award, advisor: Wei Wang, 2019.
    • Yelp dataset Challenge Winner, Round 9, Yelp, 2017.
    • Department Fellowship, University of California Los Angeles, 2013.
    • Full Postgraduate Fellowship, University of Hong Kong, 2010.
    • University and department Research Conference Grant, University of Hong Kong, 2012.
    • Outstanding Undergraduates, Nanjing University, 2010.

    Last update: 1 June, 2025