1 code implementation • 19 Feb 2024 • Puxuan Yu, Daniel Cohen, Hemank Lamba, Joel Tetreault, Alex Jaimes
The process of scale calibration in ranking systems involves adjusting the outputs of rankers to correspond with significant qualities like click-through rates or relevance, crucial for mirroring real-world value and thereby boosting the system's effectiveness and reliability.
1 code implementation • 12 Jan 2024 • Puxuan Yu, Antonio Mallia, Matthias Petri
We explore leveraging corpus-specific vocabularies that improve both efficiency and effectiveness of learned sparse retrieval systems.
no code implementations • 26 Feb 2023 • Zhiqi Huang, Puxuan Yu, James Allan
In this paper, we introduce the approach behind our submission for the MIRACL challenge, a WSDM 2023 Cup competition that centers on ad-hoc retrieval across 18 diverse languages.
no code implementations • 29 Jan 2023 • Zhiqi Huang, Puxuan Yu, James Allan
Moreover, unlike the English-to-English retrieval task, where large-scale training collections for document ranking such as MS MARCO are available, the lack of cross-lingual retrieval data for low-resource language makes it more challenging for training cross-lingual retrieval models.
no code implementations • 26 May 2020 • Puxuan Yu, James Allan
In this study, we investigate interaction-based neural matching models for ad-hoc cross-lingual information retrieval (CLIR) using cross-lingual word embeddings (CLWEs).
Cross-Lingual Information Retrieval Cross-Lingual Word Embeddings +2