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anonymous-submission-nips/mlaire-mlqa

MLAIRE-MLQA MLQA reformatted for language-aware retrieval evaluation. Passages are deduplicated at the context level via union-find on the original MLQA ids. Relevance is encoded by group_id matching. This repository is part of the MLAIRE benchmark, submitted anonymously to the NeurIPS 2026 Evaluations & Datasets Track. Authors and affiliations are withheld for double-blind review. Default top-k Reported metrics in the paper use top-20. Layout… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-submission-nips/mlaire-mlqa.

sourceHugging Facecc-by-sa-3.0updated 5mo agoView on Hugging Face

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