The SPLADE CoCondenser EnsembleDistil model is a passage retrieval system based on sparse neural IR models, which achieves state-of-the-art performance on MS MARCO dev dataset with MRR@10 of 38.3 and R@1000 of 98.3. The model uses a combination of distillation and hard negative sampling techniques to improve its effectiveness.
The SPLADE CoCondenser EnsembleDistil model is a passage retrieval system based on sparse neural IR models, which achieves state-of-the-art performance on MS MARCO dev dataset with MRR@10 of 38.3 and R@1000 of 98.3. The model uses a combination of distillation and hard negative sampling techniques to improve its effectiveness.
text prompt, should include exactly one [MASK] token
You need to login to use this model
where is my father? (0.09)
where is my mother? (0.08)
SPLADE model for passage retrieval. For additional details, please visit:
MRR@10 (MS MARCO dev) | R@1000 (MS MARCO dev) | |
---|---|---|
splade-cocondenser-ensembledistil | 38.3 | 98.3 |
If you use our checkpoint, please cite our work:
@misc{https://doi.org/10.48550/arxiv.2205.04733,
doi = {10.48550/ARXIV.2205.04733},
url = {https://arxiv.org/abs/2205.04733},
author = {Formal, Thibault and Lassance, Carlos and Piwowarski, Benjamin and Clinchant, Stéphane},
keywords = {Information Retrieval (cs.IR), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}
}