Xinyang Yi - RankMe

59 papers A* 14A 9Journal 26Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations. WWW 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, Rómer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng
2026	J	`jnl`	Vectorizing the Trie: Efficient Constrained Decoding for LLM-based Generative Retrieval on Accelerators. CoRR Zhengyang Su, Isay Katsman, Yueqi Wang, Ruining He, Lukasz Heldt, Raghunandan H. Keshavan, Shao-Chuan Wang, Xinyang Yi, Mingyan Gao, Onkar Dalal, Lichan Hong, Ed H. Chi, Ningren Han
2025	A	`conf`	Enhancing Online Ranking Systems via Multi-Surface Co-Training for Content Understanding. RecSys 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
2025	J	`jnl`	PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations. CoRR 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, Rómer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng
2025	—	`conf`	Reward Shaping for User Satisfaction. ECML/PKDD (6) Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen
2024	—	`conf`	Aligning Large Language Models with Recommendation Knowledge. NAACL-HLT (Findings) Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
2024	J	`jnl`	Aligning Large Language Models with Recommendation Knowledge. CoRR Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
2024	A	`conf`	Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. RecSys 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
2024	—	`conf`	Leveraging LLM Reasoning Enhances Personalized Recommender Systems. ACL (Findings) Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed Huai-hsin Chi, Xinyang Yi
2024	J	`jnl`	Leveraging LLM Reasoning Enhances Personalized Recommender Systems. CoRR Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed H. Chi, Xinyang Yi
2024	J	`jnl`	STAR: A Simple Training-free Approach for Recommendations using Large Language Models. CoRR Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, Lichan Hong, Ed H. Chi, Xinyang Yi
2024	A	`conf`	Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models. RecSys 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
2023	J	`jnl`	Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy
2023	J	`jnl`	Density Weighting for Multi-Interest Personalized Recommendation. CoRR Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi
2023	A*	`conf`	Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi
2023	A*	`conf`	Improving Training Stability for Multitask Ranking Models in Recommender Systems. KDD Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
2023	J	`jnl`	Improving Training Stability for Multitask Ranking Models in Recommender Systems. CoRR Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
2023	A	`conf`	Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
2023	J	`jnl`	Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
2022	A*	`conf`	Distributionally-robust Recommendations for Improving Worst-case User Experience. WWW Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi
2022	J	`jnl`	Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi
2022	A*	`conf`	Improving Multi-Task Generalization via Regularizing Spurious Correlation. NeurIPS Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
2022	J	`jnl`	Improving Multi-Task Generalization via Regularizing Spurious Correlation. CoRR Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
2022	J	`jnl`	Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen
2021	A*	`conf`	A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi
2021	A*	`conf`	Learning to Embed Categorical Features without Embedding Tables for Recommendation. KDD Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi
2021	A	`conf`	Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
2021	A	`conf`	Self-supervised Learning for Large-scale Item Recommendations. CIKM 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
2020	J	`jnl`	A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. CoRR Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi
2020	J	`jnl`	Deep Hash Embedding for Large-Vocab Categorical Feature Representations. CoRR Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi
2020	A*	`conf`	End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. WWW Jyun-Yu Jiang, Tao Wu, Georgios Roumpos, Heng-Tze Cheng, Xinyang Yi, Ed H. Chi, Harish Ganapathy, Nitin Jindal, Pei Cao, Wei Wang
2020	—	`conf`	Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. WWW (Companion Volume) Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi
2020	J	`jnl`	Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. CoRR Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi
2020	J	`jnl`	Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
2020	—	`conf`	Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. WWW (Companion Volume) Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, Ed H. Chi
2020	A*	`conf`	Off-policy Learning in Two-stage Recommender Systems. WWW Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi
2020	J	`jnl`	Self-supervised Learning for Deep Models in Recommendations. CoRR Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger
2019	—	`conf`	Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
2019	J	`jnl`	More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
2019	A	`conf`	Recommending what video to watch next: a multitask ranking system. RecSys Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi
2019	A	`conf`	Sampling-bias-corrected neural modeling for large corpus item recommendations. RecSys Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi
2018	J	`jnl`	Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates. IEEE Trans. Inf. Theory Yudong Chen, Xinyang Yi, Constantine Caramanis
2018	J	`jnl`	Efficient Training on Very Large Corpora via Gramian Estimation. CoRR Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
2018	A*	`conf`	Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. KDD Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi
2017	A	`conf`	Minimax Gaussian Classification & Clustering. AISTATS Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar
2016	—	`conf`	Fast Algorithms for Robust PCA via Gradient Descent. NIPS Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis
2016	J	`jnl`	Fast Algorithms for Robust PCA via Gradient Descent. CoRR Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis
2016	—	`conf`	More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. NIPS Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
2016	J	`jnl`	Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization. CoRR Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
2015	A*	`conf`	Binary Embedding: Fundamental Limits and Fast Algorithm. ICML Xinyang Yi, Constantine Caramanis, Eric Price
2015	J	`jnl`	Binary Embedding: Fundamental Limits and Fast Algorithm. CoRR Xinyang Yi, Constantine Caramanis, Eric Price
2015	A*	`conf`	Novel power grid reduction method based on L1 regularization. DAC Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis
2015	—	`conf`	Optimal Linear Estimation under Unknown Nonlinear Transform. NIPS Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
2015	J	`jnl`	Optimal linear estimation under unknown nonlinear transform. CoRR Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
2015	J	`jnl`	Regularized EM Algorithms: A Unified Framework and Provable Statistical Guarantees. CoRR Xinyang Yi, Constantine Caramanis
2015	—	`conf`	Regularized EM Algorithms: A Unified Framework and Statistical Guarantees. NIPS Xinyang Yi, Constantine Caramanis
2014	A*	`conf`	A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates. COLT Yudong Chen, Xinyang Yi, Constantine Caramanis
2014	A*	`conf`	Alternating Minimization for Mixed Linear Regression. ICML Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
2013	J	`jnl`	A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise. CoRR Yudong Chen, Xinyang Yi, Constantine Caramanis