Beyond Ranked Lists: The SARAL Framework for Cross-Lingual Document Set Retrieval

Shantanu Agarwal, Joel Barry, Elizabeth Boschee, Scott Miller
11/5/2025
cs.CLcs.IR

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Abstract

Machine Translation for English Retrieval of Information in Any Language (MATERIAL) is an IARPA initiative targeted to advance the state of cross-lingual information retrieval (CLIR). This report provides a detailed description of Information Sciences Institute's (ISI's) Summarization and domain-Adaptive Retrieval Across Language's (SARAL's) effort for MATERIAL. Specifically, we outline our team's novel approach to handle CLIR with emphasis in developing an approach amenable to retrieve a query-relevant document \textit{set}, and not just a ranked document-list. In MATERIAL's Phase-3 evaluations, SARAL exceeded the performance of other teams in five out of six evaluation conditions spanning three different languages (Farsi, Kazakh, and Georgian).

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@article{agarwal2025beyond,
  title  = {Beyond Ranked Lists: The SARAL Framework for Cross-Lingual Document Set Retrieval},
  author = {Shantanu Agarwal and Joel Barry and Elizabeth Boschee and Scott Miller},
  year   = {2025},
  eprint = {2511.03228},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.03228v1}
}

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