Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins.

Lukas Gienapp|Niklas Deckers|Martin Potthast|Harrisen Scells


Anthology ID:DBLP:conf/ictir/GienappDPS25
Volume:Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025
Year:2025
Venue:International Conference on the Theory of Information Retrieval (ICTIR)
Publisher:ACM
Pages:275-285
URL:https://doi.org/10.1145/3731120.3744594
DOI:https://doi.org/10.1145/3731120.3744594
DBLP:conf/ictir/GienappDPS25
BibTeX:
@inproceedings{gienapp-2025-learning, author = {Lukas Gienapp and Niklas Deckers and Martin Potthast and Harrisen Scells}, editor = {Hamed Zamani and Laura Dietz and Benjamin Piwowarski and Sebastian Bruch}, title = {{Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins}}, booktitle = {{Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025}}, pages = {275--285}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3731120.3744594}, doi = {https://doi.org/10.1145/3731120.3744594} }