Yanshuai Cao 曹颜帅

Senior Director, Research & Distinguished Engineer @ RBC Borealis

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I build AI solutions that generate value for others, and conduct fundamental research and write classical style Chinese poems as creative outlets for myself.

At RBC Borealis, my job is “simple”: 1) find ways AI can create or optimize value, 2) scale teams, technology, and business to make it happen.

Most of my product work is confidential, so this site focuses on research, blog and publications that I can share, and my poems (颜辞).

news

Dec 01, 2024 Presenting 2 conference papers and 1 workshop paper at NeurIPS 2024!
Dec 01, 2024 EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation with Yuqiao Wen and others is accepted by AAAI 2025!
Oct 01, 2024 I’m awarded the Distinguished Engineer title by RBC. :tada:
Jul 01, 2024 I’m promoted to Senior Director, Research @ RBC Borealis. :tada:

latest posts

selected publications

  1. Preprint
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    NeuZip: Memory-Efficient Training and Inference with Dynamic Compression of Neural Networks
    Yongchang Hao, Yanshuai Cao, and Lili Mou
    arXiv preprint arXiv:2410.20650, 2024
  2. NeurIPS
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    Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models
    Sadegh Mahdavi, Raquel Aoki, Keyi Tang, and Yanshuai Cao
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  3. NeurIPS
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    Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
    Zichao Li, Yanshuai Cao, and Jackie CK Cheung
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  4. ACL
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    Jump Starting Bandits with LLM-Generated Prior Knowledge
    Parand A. Alamdari, Yanshuai Cao, and Kevin H. Wilson
    In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Nov 2024
  5. ICML
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    Flora: Low-Rank Adapters Are Secretly Gradient Compressors
    Yongchang Hao, Yanshuai Cao, and Lili Mou
    In Forty-first International Conference on Machine Learning, Nov 2024
  6. ACL
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    Code Generation from Natural Language with Less Prior Knowledge and More Monolingual Data
    Sajad Norouzi, Keyi Tang, and Yanshuai Cao
    In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, Aug 2021
  7. ACL
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    Optimizing Deeper Transformers on Small Datasets
    Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi, Keyi Tang, Chenyang Huang, Jackie Chi Kit Cheung, Simon J.D. Prince, and Yanshuai Cao
    In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, Aug 2021
  8. AISTATS
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    Better Long-Range Dependency By Bootstrapping A Mutual Information Regularizer
    Yanshuai Cao*, and Peng Xu*
    In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, 26–28 aug 2020
  9. ICML
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    Evaluating Lossy Compression Rates of Deep Generative Models
    Sicong Huang*, Alireza Makhzani*Yanshuai Cao, and Roger Grosse
    In Proceedings of the 37th International Conference on Machine Learning, 13–18 jul 2020
  10. ICML
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    On Variational Learning of Controllable Representations for Text without Supervision
    Peng Xu, Jackie Chi Kit Cheung, and Yanshuai Cao
    In Proceedings of the 37th International Conference on Machine Learning, 13–18 jul 2020
  11. ICLR
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    Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
    Yanshuai Cao, Gavin Weiguang Ding, Kry Yik-Chau Lui, and Ruitong Huang
    International Conference on Learning Representations, 13–18 jul 2018
  12. PhD Thesis
    Scaling Gaussian Processes
    Yanshuai Cao
    13–18 jul 2018
  13. ICLR
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    Adversarial Manipulation of Deep Representations
    Sara Sabour*Yanshuai Cao*, Fartash Faghri, and David J. Fleet
    13–18 jul 2016
  14. NeurIPS
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    Efficient Optimization for Sparse Gaussian Process Regression
    Yanshuai Cao, Marcus A Brubaker, David J Fleet, and Aaron Hertzmann
    In Advances in Neural Information Processing Systems, 13–18 jul 2013