Column Sampling Based Discrete Supervised Hashing. - Wang-Cheng Kang; Wu-Jun Li; Zhi-Hua Zhou (AAAI, 2016)

Feature Learning Based Deep Supervised Hashing with Pairwise Labels. - Wu-Jun Li; Sheng Wang; Wang-Cheng Kang (IJCAI, 2016)

Visually-Aware Fashion Recommendation and Design with Generative Image Models. - Wang-Cheng Kang; Chen Fang; Zhaowen Wang; Julian J. McAuley (ICDM, 2017)

Translation-based Recommendation. - Ruining He; Wang-Cheng Kang; Julian J. McAuley (RecSys, 2017)

Recommendation Through Mixtures of Heterogeneous Item Relationships. - Wang-Cheng Kang; Mengting Wan; Julian J. McAuley (CIKM, 2018)

Self-Attentive Sequential Recommendation. - Wang-Cheng Kang; Julian J. McAuley (ICDM, 2018)

Translation-based Recommendation: A Scalable Method for Modeling Sequential Behavior. - Ruining He; Wang-Cheng Kang; Julian J. McAuley (IJCAI, 2018)

Learning consumer and producer embeddings for user-generated content recommendation. - Wang-Cheng Kang; Julian J. McAuley (RecSys, 2018)

Candidate Generation with Binary Codes for Large-Scale Top-N Recommendation. - Wang-Cheng Kang; Julian John McAuley (CIKM, 2019)

CosRec: 2D Convolutional Neural Networks for Sequential Recommendation. - An Yan 003; Shuo Cheng; Wang-Cheng Kang; Mengting Wan; Julian J. McAuley (CIKM, 2019)

Complete the Look: Scene-Based Complementary Product Recommendation. - Wang-Cheng Kang; Eric Kim; Jure Leskovec; Charles Rosenberg 001; Julian J. McAuley (CVPR, 2019)

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 (WWW (Companion Volume), 2020)

Deep Hash Embedding for Large-Vocab Categorical Feature Representations. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Ting Chen; Lichan Hong; Ed H. Chi (CoRR, 2020)

Building Visually-aware, Dynamic, and Efficient Recommender Systems - Wang-Cheng Kang (2020)

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 (KDD, 2021)

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. - Benjamin Coleman; Wang-Cheng Kang; Matthew Fahrbach; Ruoxi Wang; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (NeurIPS, 2023)

Efficient Data Representation Learning in Google-scale Systems. - Derek Zhiyuan Cheng; Ruoxi Wang; Wang-Cheng Kang; Benjamin Coleman; Yin Zhang 011; Jianmo Ni; Jonathan Valverde; Lichan Hong; Ed H. Chi (RecSys, 2023)

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. - Wang-Cheng Kang; Jianmo Ni; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (CoRR, 2023)

Farzi Data: Autoregressive Data Distillation. - Noveen Sachdeva; Zexue He; Wang-Cheng Kang; Jianmo Ni; Derek Zhiyuan Cheng; Julian J. McAuley (CoRR, 2023)

First Workshop on Generative AI for Recommender Systems and Personalization. - Narges Tabari; Aniket Anand Deshmukh; Wang-Cheng Kang; Hamed Zamani; Rashmi Gangadharaiah; Julian J. McAuley; George Karypis (KDD, 2024)

Improving Data Efficiency for Recommenders and LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; James Caverlee; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

How to Train Data-Efficient LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; Lichan Hong; Ed H. Chi; James Caverlee; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2024)

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation. - Yupeng Hou; Jianmo Ni; Zhankui He; Noveen Sachdeva; Wang-Cheng Kang; Ed H. Chi; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2025)