5 citations · 5 across the 1 of their papers we have counts for
10 papers
kANNolo: Sweet and Smooth Approximate k-Nearest Neighbors Search
Leonardo Delfino, Domenico Erriquez, Silvio Martinico +3
Approximate Nearest Neighbors (ANN) search is a crucial task in several applications like recommender systems and information retrieval. Current state-of-the-art ANN libraries, alt…
Efficient Multivector Retrieval with Token-Aware Clustering and Hierarchical Indexing
Silvio Martinico, Franco Maria Nardini, Cosimo Rulli +1
Multivector retrieval models achieve state-of-the-art effectiveness through fine-grained token-level representations, but their deployment incurs substantial computational and memo…
Sparton: Fast and Memory-Efficient Triton Kernel for Learned Sparse Retrieval
Thong Nguyen, Cosimo Rulli, Franco Maria Nardini +2
State-of-the-art Learned Sparse Retrieval (LSR) models, such as Splade, typically employ a Language Modeling (LM) head to project latent hidden states into a lexically-anchored log…
Forward Index Compression for Learned Sparse Retrieval
Sebastian Bruch, Martino Fontana, Franco Maria Nardini +2
Text retrieval using learned sparse representations of queries and documents has, over the years, evolved into a highly effective approach to search. It is thanks to recent advance…
Gender Disparities in StackOverflow's Community-Based Question Answering: A Matter of Quantity versus Quality
Maddalena Amendola, Cosimo Rulli, Carlos Castillo +2
Community Question-Answering platforms, such as Stack Overflow (SO), are valuable knowledge exchange and problem-solving resources. These platforms incorporate mechanisms to assess…
Multivector Reranking in the Era of Strong First-Stage Retrievers
Silvio Martinico, Franco Maria Nardini, Cosimo Rulli +1
Learned multivector representations power modern search systems with strong retrieval effectiveness, but their real-world use is limited by the high cost of exhaustive token-level…