108 citations · 370 across the 13 of their papers we have counts for
13 papers
Caching Historical Embeddings in Conversational Search
Ophir Frieder, Ida Mele, Cristina Ioana Muntean +3
Rapid response, namely low latency, is fundamental in search applications; it is particularly so in interactive search sessions, such as those encountered in conversational setting…
Faster Learned Sparse Retrieval with Guided Traversal
Antonio Mallia, Joel Mackenzie, Torsten Suel +1
Neural information retrieval architectures based on transformers such as BERT are able to significantly improve system effectiveness over traditional sparse models such as BM25. Th…
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval
Craig Macdonald, Nicola Tonellotto
Dense retrieval, which describes the use of contextualised language models such as BERT to identify documents from a collection by leveraging approximate nearest neighbour (ANN) te…
Query Embedding Pruning for Dense Retrieval
Nicola Tonellotto, Craig Macdonald
Recent advances in dense retrieval techniques have offered the promise of being able not just to re-rank documents using contextualised language models such as BERT, but also to us…
On Single and Multiple Representations in Dense Passage Retrieval
Craig Macdonald, Nicola Tonellotto, Iadh Ounis
The advent of contextualised language models has brought gains in search effectiveness, not just when applied for re-ranking the output of classical weighting models such as BM25,…
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
Xiao Wang, Craig Macdonald, Nicola Tonellotto +1
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have shown the usefulness of expanding and reweighting the users' initial queries using information occu…