Philipp Hager

Orcid: 0000-0001-5696-9732

Affiliations:
  • University of Amsterdam, Mercury Machine Learning Lab, Amsterdam, The Netherlands
  • Hasso Plattner Institute, Potsdam, Germany (2017 - 2020)


According to our database1, Philipp Hager authored at least 13 papers between 2021 and 2025.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
CLAX: Fast and Flexible Neural Click Models in JAX.
CoRR, November, 2025

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank (Extended Abstract).
CoRR, August, 2025

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank.
Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, 2025

2024
Understanding the Effects of the Baidu-ULTR Logging Policy on Two-Tower Models.
CoRR, 2024

Unbiased Learning to Rank: On Recent Advances and Practical Applications.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

2023
Report on the 1st Workshop on Generative Information Retrieval (Gen-IR 2023) at SIGIR 2023.
SIGIR Forum, December, 2023

Recent Advances in the Foundations and Applications of Unbiased Learning to Rank.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

An Offline Metric for the Debiasedness of Click Models.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Collaborative filtering algorithms are prone to mainstream-taste bias.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Recent Advancements in Unbiased Learning to Rank.
Proceedings of the 15th Annual Meeting of the Forum for Information Retrieval Evaluation, 2023

Contrasting Neural Click Models and Pointwise IPS Rankers.
Proceedings of the Advances in Information Retrieval, 2023

2021
Multifaceted Domain-Specific Document Embeddings.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations, 2021


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