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Papers/SPLADE-v3: New baselines for SPLADE

SPLADE-v3: New baselines for SPLADE

Carlos Lassance, Hervé Déjean, Thibault Formal, Stéphane Clinchant

2024-03-11Sentence RetrievalZero Shot on BEIR (Inference Free Model)Passage Retrieval
PaperPDFCode

Abstract

A companion to the release of the latest version of the SPLADE library. We describe changes to the training structure and present our latest series of models -- SPLADE-v3. We compare this new version to BM25, SPLADE++, as well as re-rankers, and showcase its effectiveness via a meta-analysis over more than 40 query sets. SPLADE-v3 further pushes the limit of SPLADE models: it is statistically significantly more effective than both BM25 and SPLADE++, while comparing well to cross-encoder re-rankers. Specifically, it gets more than 40 MRR@10 on the MS MARCO dev set, and improves by 2% the out-of-domain results on the BEIR benchmark.

Results

TaskDatasetMetricValueModel
Information RetrievalPeerQAMRR0.4536SPLADEv3
Information RetrievalPeerQARecall@100.6851SPLADEv3
Information RetrievalBEIRNCDG@1046.97SPLADEv3-Doc

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