NARDINI, FRANCO MARIA
NARDINI, FRANCO MARIA
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
A learning-to-rank formulation of clustering-based approximate nearest neighbor search
2024 Vecchiato, T.; Lucchese, C.; Nardini, F. M.; Bruch, S.
Bridging dense and sparse maximum inner product search
2024 Bruch, S.; Nardini, F. M.; Ingber, A.; Liberty, E.
Caching historical embeddings in conversational search
2024 Frieder, O.; Mele, I.; Muntean, C.; Nardini, F. M.; Perego, R.; Tonellotto, N.
Distilled neural networks for efficient learning to rank: (Extended Abstract)
2024 Nardini, F. M.; Rulli, C.; Trani, S.; Venturini, R.
Early exit strategies for approximate k-NN search in dense retrieval
2024 Busolin, F.; Lucchese, C.; Nardini, F. M.; Orlando, S.; Perego, R.; Trani, S.
Efficient and effective multi-vector dense retrieval with EMVB
2024 Nardini, F. M.; Rulli, C.; Venturini, R.
Efficient inverted indexes for approximate retrieval over learned sparse representations
2024 Bruch, S.; Nardini, F. M.; Rulli, C.; Venturini, R.
Efficient multi-vector dense retrieval with bit vectors
2024 Nardini, F. M.; Rulli, C.; Venturini, R.
Improving RAG systems via sentence clustering and reordering
2024 Alessio, M.; Faggioli, G.; Ferro, N.; Nardini, F. M.; Perego, R.
Learning bivariate scoring functions for ranking
2024 Nardini, F. M.; Trani, R.; Venturini, R.
LongDoc summarization using instruction-tuned large language models for food safety regulations
2024 Rocchietti, G.; Rulli, C.; Randl, K.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S.; Karvounis, M.; Janostik, J.
Pairing clustered inverted indexes with κ-NN graphs for fast approximate retrieval over learned sparse representations
2024 Bruch, S.; Nardini, F. M.; Rulli, C.; Venturini, R.
ReNeuIR at SIGIR 2024: the third workshop on reaching efficiency in neural information retrieval
2024 Fröbe, M.; Mackenzie, J.; Mitra, B.; Nardini, F. M.; Potthast, M.
Report on the 13th Italian Information Retrieval Workshop (IIR 2023)
2024 Faggioli, G.; Ferrara, A.; Nardini, F. M.; Tonellotto, N.
Special section on efficiency in neural information retrieval
2024 Bruch, S.; Lucchese, C.; Maistro, M.; Nardini, F. M.
An approximate algorithm for maximum inner product search over streaming sparse vectors
2023 Bruch S.; Nardini F.M.; Ingber A.; Liberty E.
An optimal algorithm for finding champions in tournament graphs
2023 Beretta, L.; Nardini, F. M.; Trani, R.; Venturini, R.
Can embeddings analysis explain large language model ranking?
2023 Lucchese, C; Minello, G; Nardini, Fm; Orlando, S; Perego, R; Veneri, A
Commonsense injection in conversational systems: an adaptable framework for query expansion
2023 Rocchietti, G.; Frieder, O.; Muntean, CRISTINA-IOANA; Nardini, F. M.; Perego, R.
Early exit strategies for learning-to-rank cascades
2023 Busolin, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| A learning-to-rank formulation of clustering-based approximate nearest neighbor search | 1-gen-2024 | Vecchiato, T.; Lucchese, C.; Nardini, F. M.; Bruch, S. | |
| Bridging dense and sparse maximum inner product search | 1-gen-2024 | Bruch, S.; Nardini, F. M.; Ingber, A.; Liberty, E. | |
| Caching historical embeddings in conversational search | 1-gen-2024 | Frieder, O.; Mele, I.; Muntean, C.; Nardini, F. M.; Perego, R.; Tonellotto, N. | |
| Distilled neural networks for efficient learning to rank: (Extended Abstract) | 1-gen-2024 | Nardini, F. M.; Rulli, C.; Trani, S.; Venturini, R. | |
| Early exit strategies for approximate k-NN search in dense retrieval | 1-gen-2024 | Busolin, F.; Lucchese, C.; Nardini, F. M.; Orlando, S.; Perego, R.; Trani, S. | |
| Efficient and effective multi-vector dense retrieval with EMVB | 1-gen-2024 | Nardini, F. M.; Rulli, C.; Venturini, R. | |
| Efficient inverted indexes for approximate retrieval over learned sparse representations | 1-gen-2024 | Bruch, S.; Nardini, F. M.; Rulli, C.; Venturini, R. | |
| Efficient multi-vector dense retrieval with bit vectors | 1-gen-2024 | Nardini, F. M.; Rulli, C.; Venturini, R. | |
| Improving RAG systems via sentence clustering and reordering | 1-gen-2024 | Alessio, M.; Faggioli, G.; Ferro, N.; Nardini, F. M.; Perego, R. | |
| Learning bivariate scoring functions for ranking | 1-gen-2024 | Nardini, F. M.; Trani, R.; Venturini, R. | |
| LongDoc summarization using instruction-tuned large language models for food safety regulations | 1-gen-2024 | Rocchietti, G.; Rulli, C.; Randl, K.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S.; Karvounis, M.; Janostik, J. | |
| Pairing clustered inverted indexes with κ-NN graphs for fast approximate retrieval over learned sparse representations | 1-gen-2024 | Bruch, S.; Nardini, F. M.; Rulli, C.; Venturini, R. | |
| ReNeuIR at SIGIR 2024: the third workshop on reaching efficiency in neural information retrieval | 1-gen-2024 | Fröbe, M.; Mackenzie, J.; Mitra, B.; Nardini, F. M.; Potthast, M. | |
| Report on the 13th Italian Information Retrieval Workshop (IIR 2023) | 1-gen-2024 | Faggioli, G.; Ferrara, A.; Nardini, F. M.; Tonellotto, N. | |
| Special section on efficiency in neural information retrieval | 1-gen-2024 | Bruch, S.; Lucchese, C.; Maistro, M.; Nardini, F. M. | |
| An approximate algorithm for maximum inner product search over streaming sparse vectors | 1-gen-2023 | Bruch S.; Nardini F.M.; Ingber A.; Liberty E. | |
| An optimal algorithm for finding champions in tournament graphs | 1-gen-2023 | Beretta, L.; Nardini, F. M.; Trani, R.; Venturini, R. | |
| Can embeddings analysis explain large language model ranking? | 1-gen-2023 | Lucchese, C; Minello, G; Nardini, Fm; Orlando, S; Perego, R; Veneri, A | |
| Commonsense injection in conversational systems: an adaptable framework for query expansion | 1-gen-2023 | Rocchietti, G.; Frieder, O.; Muntean, CRISTINA-IOANA; Nardini, F. M.; Perego, R. | |
| Early exit strategies for learning-to-rank cascades | 1-gen-2023 | Busolin, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S |