This paper describes our participation in the 2023 WSDM CUP - MIRACL challenge. Via a combination of i) document translation; ii) multilingual SPLADE and Contriever; and iii) multilingual RankT5 and many other models, we were able to get first place in both the known and surprise languages tracks. Our strategy mostly revolved around getting the most diverse runs for the first stage and then throwing all possible reranking techniques. While this was not a first for many techniques, we had some things that we believe were never tried before, for example, we train the first SPLADE model that is effectively capable of working in more than 10 languages. However, a more careful study of the results is needed in order to verify if we were able to get first place just due to brute force or if the hybrids we developed really brought improvements over the other team's solutions.

翻译：本文介绍了我们参与2023年WSDM CUP - MIRACL挑战赛的情况。通过结合以下技术：i) 文档翻译；ii) 多语言SPLADE和Contriever；iii) 多语言RankT5及其他多种模型，我们成功在已知语言和惊喜语言两个赛道均获得第一名。我们的策略主要围绕第一阶段获取最多样化的检索结果，随后应用所有可能的重新排序技术。尽管这些技术大多并非首创，但我们也尝试了一些此前未曾有过的方法，例如，我们训练了首个能够有效在十种以上语言中运行的SPLADE模型。然而，仍需对结果进行更仔细的研究，以验证我们获得第一名是否仅凭蛮力，还是我们开发的混合方案确实优于其他团队的解决方案。