SPLADE-v3: New baselines for SPLADE
This work provides incremental improvements to SPLADE models for information retrieval tasks, benefiting researchers and practitioners in search and NLP.
The authors introduced SPLADE-v3, an improved version of the SPLADE model for information retrieval, achieving statistically significant gains over BM25 and SPLADE++ with over 40 MRR@10 on MS MARCO and a 2% improvement on BEIR benchmarks.
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.