4 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
WebFAQ 2.0: A Multilingual QA Dataset with Mined Hard Negatives for Dense Retrieval
Michael Dinzinger, Laura Caspari, Ali Salman +3
We introduce WebFAQ 2.0, a new version of the WebFAQ dataset, containing 198 million FAQ-based natural question-answer pairs across 108 languages. Compared to the previous version,…
CoRECT: A Framework for Evaluating Embedding Compression Techniques at Scale
L. Caspari, M. Dinzinger, K. Ghosh Dastidar +3
Dense retrieval systems have proven to be effective across various benchmarks, but require substantial memory to store large search indices. Recent advances in embedding compressio…
Beyond Benchmarks: Evaluating Embedding Model Similarity for Retrieval Augmented Generation Systems
Laura Caspari, Kanishka Ghosh Dastidar, Saber Zerhoudi +2
The choice of embedding model is a crucial step in the design of Retrieval Augmented Generation (RAG) systems. Given the sheer volume of available options, identifying clusters of…