Zhiyuan Cheng

Orcid: 0009-0000-7943-8328

Affiliations:
  • Google


According to our database1, Zhiyuan Cheng authored at least 22 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
How to Train Data-Efficient LLMs.
CoRR, 2024

2023
Farzi Data: Autoregressive Data Distillation.
CoRR, 2023

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction.
CoRR, 2023

HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Efficient Data Representation Learning in Google-scale Systems.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN).
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
An Online Multi-task Learning Framework for Google Feed Ads Auction Models.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation.
Proceedings of the WWW '21: The Web Conference 2021, 2021

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems.
Proceedings of the WSDM '21, 2021

Learning to Embed Categorical Features without Embedding Tables for Recommendation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Self-supervised Learning for Large-scale Item Recommendations.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Deep Hash Embedding for Large-Vocab Categorical Feature Representations.
CoRR, 2020

DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems.
CoRR, 2020

Self-supervised Learning for Deep Models in Recommendations.
CoRR, 2020

Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

2019
Sampling-bias-corrected neural modeling for large corpus item recommendations.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

2017
Beyond Globally Optimal: Focused Learning for Improved Recommendations.
Proceedings of the 26th International Conference on World Wide Web, 2017

2015
Improving User Topic Interest Profiles by Behavior Factorization.
Proceedings of the 24th International Conference on World Wide Web, 2015


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