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A companion to the release of the latest version of the SPLADE library.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter, 10 2019
V. Sanh, L. Debut, J. Chaumond, and T. Wolf · 2019
Earlier work this paper cites.
Distilling dense representations for ranking using tightly-coupled teachers, 2020
S.-C. Lin, J.-H. Yang, and J. Lin · 2020
Earlier work this paper cites.
Splade v2: Sparse lexical and expansion model for information retrieval, 2021
T. Formal, C. Lassance, B. Piwowarski, and S. Clinchant · 2021
Earlier work this paper cites.
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
T. Formal, B. Piwowarski, and S. Clinchant · 2021
Earlier work this paper cites.
Improving efficient neural ranking models with cross-architecture knowledge distillation, 2021
S. Hofstätter, S. Althammer, M. Schröder, M. Sertkan, and A. Hanbury · 2021
Earlier work this paper cites.
Simplified data wrangling with ir_datasets
S. MacAvaney, A. Yates, S. Feldman, D. Downey, A. Cohan, and N. Goharian · 2021
Earlier work this paper cites.
Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
N. Thakur, N. Reimers, A. Rücklé, A. Srivastava, and I. Gurevych · 2021
Earlier work this paper cites.
ranx: A blazing-fast python library for ranking evaluation and comparison
E. Bassani · 2022
Cited alongside, same era.
Overview of the trec 2022 deep learning track
N. Craswell, B. Mitra, E. Yilmaz, D. F. Campos, J. Lin, E. M. Voorhees, and I. Soboroff · 2022
Cited alongside, same era.
From distillation to hard negative sampling: Making sparse neural ir models more effective
T. Formal, C. Lassance, B. Piwowarski, and S. Clinchant · 2022
Cited alongside, same era.
Unsupervised corpus aware language model pre-training for dense passage retrieval
L. Gao and J. Callan · 2022
Cited alongside, same era.
Tevatron: An efficient and flexible toolkit for dense retrieval
L. Gao, X. Ma, J. Lin, and J. Callan · 2022
Cited alongside, same era.
An efficiency study for splade models
Curriculum learning for dense retrieval distillation
H. Zeng, H. Zamani, and V. Vinay · 2022
Later among the works it cites.
Benchmarking middle-trained language models for neural search
H. Déjean, S. Clinchant, C. Lassance, S. Lupart, and T. Formal · 2023
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Towards effective and efficient sparse neural information retrieval
T. Formal, C. Lassance, B. Piwowarski, and S. Clinchant · 2023
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The tale of two ms marco – and their unfair comparisons, 2023
C. Lassance and S. Clinchant · 2023
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The tale of two msmarco - and their unfair comparisons
C. Lassance and S. Clinchant · 2023
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Ranger: A toolkit for effect-size based multi-task evaluation
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C. Lassance and S. Clinchant · 2022
Cited alongside, same era.
ColBERTv2: Effective and efficient retrieval via lightweight late interaction
K. Santhanam, O. Khattab, J. Saad-Falcon, C. Potts, and M. Zaharia · 2022
Cited alongside, same era.
M. Sertkan, S. Althammer, and S. Hofstätter · 2023
Later among the works it cites.
Exploring effect-size-based meta-analysis for multi-dataset evaluation
M. Sertkan, S. Althammer, S. Hofstätter, P. Knees, and J. Neidhardt · 2023
Later among the works it cites.