Lukasz Heldt
Google (United States)(US)
Publications by Year
Research Areas
Recommender Systems and Techniques, Topic Modeling, Advanced Bandit Algorithms Research, Natural Language Processing Techniques, Decision-Making and Behavioral Economics
Most-Cited Works
- → Sampling-bias-corrected neural modeling for large corpus item recommendations(2019)203 cited
- → HYDRAstor: a Scalable Secondary Storage(2009)200 cited
- → Recommender Systems with Generative Retrieval(2023)27 cited
- → Fairness in Recommendation Ranking through Pairwise Comparisons(2019)24 cited
- → Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations(2024)18 cited
- → Long-Term Value of Exploration: Measurements, Findings and Algorithms(2024)12 cited
- → Online Matching: A Real-time Bandit System for Large-scale Recommendations(2023)9 cited
- → Aligning Large Language Models with Recommendation Knowledge(2024)7 cited
- → Enhancing Online Ranking Systems via Multi-Surface Co-Training for Content Understanding(2025)