Xinyang Yi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
27
Venues
11
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
27 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | WWW | PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations. | Ruining He, Lukasz Heldt, Lichan Hong, Raghunandan H. Keshavan, Shifan Mao, Nikhil Mehta, Zhengyang Su, Alicia Tsai, Yueqi Wang, Shao-Chuan Wang, Xinyang Yi, Lexi Baugher, Baykal Cakici, Ed H. Chi, Cristos Goodrow, Ningren Han, He Ma, Rmer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng |
| 2025 | RecSys | Enhancing Online Ranking Systems via Multi-Surface Co-Training for Content Understanding. | Gwendolyn Zhao, Yilin Zheng, Raghu Keshavan, Lukasz Heldt, Qian Sun, Fabio Soldo, Li Wei, Aniruddh Nath, Nikhil Khani, Weilong Yang, Dapo Omidiran, Rein Zhang, Mei Chen, Lichan Hong, Xinyang Yi |
| 2024 | ACL | Leveraging LLM Reasoning Enhances Personalized Recommender Systems. | Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed Huai-hsin Chi, Xinyang Yi |
| 2024 | NAACL | Aligning Large Language Models with Recommendation Knowledge. | Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy |
| 2024 | RecSys | Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models. | Yuening Li, Diego Uribe, Chuan He, Jiaxi Tang, Qingyun Liu, Junjie Shan, Ben Most, Kaushik Kalyan, Shuchao Bi, Xinyang Yi, Lichan Hong, Ed H. Chi, Liang Liu |
| 2024 | RecSys | Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. | Anima Singh, Trung Vu, Nikhil Mehta, Raghunandan H. Keshavan, Maheswaran Sathiamoorthy, Yilin Zheng, Lichan Hong, Lukasz Heldt, Li Wei, Devansh Tandon, Ed H. Chi, Xinyang Yi |
| 2023 | KDD | Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). | Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi |
| 2023 | KDD | Improving Training Stability for Multitask Ranking Models in Recommender Systems. | Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi |
| 2023 | RecSys | Online Matching: A Real-time Bandit System for Large-scale Recommendations. | Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi |
| 2022 | WWW | Distributionally-robust Recommendations for Improving Worst-case User Experience. | Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi |
| 2021 | AISTATS | Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. | Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei |
| 2021 | CIKM | Self-supervised Learning for Large-scale Item Recommendations. | Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger |
| 2021 | KDD | Learning to Embed Categorical Features without Embedding Tables for Recommendation. | Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi |
| 2021 | WWW | A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. | Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi |
| 2020 | WWW | End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. | Jyun-Yu Jiang, Tao Wu, Georgios Roumpos, Heng-Tze Cheng, Xinyang Yi, Ed H. Chi, Harish Ganapathy, Nitin Jindal, Pei Cao, Wei Wang |
| 2020 | WWW | Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. | Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi |
| 2020 | WWW | Off-policy Learning in Two-stage Recommender Systems. | Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi |
| 2020 | WWW | Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. | Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, Ed H. Chi |
| 2019 | ICLR | Efficient Training on Very Large Corpora via Gramian Estimation. | Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson |
| 2019 | RecSys | Sampling-bias-corrected neural modeling for large corpus item recommendations. | Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi |
| 2019 | RecSys | Recommending what video to watch next: a multitask ranking system. | Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi |
| 2018 | KDD | Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. | Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi |
| 2017 | AISTATS | Minimax Gaussian Classification & Clustering. | Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar |
| 2015 | DAC | Novel power grid reduction method based on L1 regularization. | Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis |
| 2015 | ICML | Binary Embedding: Fundamental Limits and Fast Algorithm. | Xinyang Yi, Constantine Caramanis, Eric Price |
| 2014 | COLT | A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates. | Yudong Chen, Xinyang Yi, Constantine Caramanis |
| 2014 | ICML | Alternating Minimization for Mixed Linear Regression. | Xinyang Yi, Constantine Caramanis, Sujay Sanghavi |