--- license: mit language: - ar - de - nl - en - es - fr - hi - id - it - ja - pt - ru - vi - zh task_categories: - text-retrieval pretty_name: MLIR Benchmarks configs: - config_name: MLIR-en_Belebele default: true data_files: - split: queries path: viewer/MLIR-en/Belebele_test/queries.jsonl - split: corpus path: viewer/MLIR-en/Belebele_test/corpus.jsonl - config_name: MLIR-en_MLQA data_files: - split: queries path: viewer/MLIR-en/MLQA_test/queries.jsonl - split: corpus path: viewer/MLIR-en/MLQA_test/corpus.jsonl - config_name: MLIR-en_MultiEup data_files: - split: queries path: viewer/MLIR-en/MultiEup_test/queries.jsonl - split: corpus path: viewer/MLIR-en/MultiEup_test/corpus.jsonl - config_name: MLIR-en_XQuAD data_files: - split: queries path: viewer/MLIR-en/XQuAD_test/queries.jsonl - split: corpus path: viewer/MLIR-en/XQuAD_test/corpus.jsonl - config_name: MLIR-zh_Belebele data_files: - split: queries path: viewer/MLIR-zh/Belebele_test/queries.jsonl - split: corpus path: viewer/MLIR-zh/Belebele_test/corpus.jsonl - config_name: MLIR-zh_MLQA data_files: - split: queries path: viewer/MLIR-zh/MLQA_test/queries.jsonl - split: corpus path: viewer/MLIR-zh/MLQA_test/corpus.jsonl - config_name: MLIR-zh_XQuAD data_files: - split: queries path: viewer/MLIR-zh/XQuAD_test/queries.jsonl - split: corpus path: viewer/MLIR-zh/XQuAD_test/corpus.jsonl - config_name: MLIR-vi_Belebele data_files: - split: queries path: viewer/MLIR-vi/Belebele_test/queries.jsonl - split: corpus path: viewer/MLIR-vi/Belebele_test/corpus.jsonl - config_name: MLIR-vi_MLQA data_files: - split: queries path: viewer/MLIR-vi/MLQA_test/queries.jsonl - split: corpus path: viewer/MLIR-vi/MLQA_test/corpus.jsonl - config_name: MLIR-vi_XQuAD data_files: - split: queries path: viewer/MLIR-vi/XQuAD_test/queries.jsonl - split: corpus path: viewer/MLIR-vi/XQuAD_test/corpus.jsonl - config_name: MLIR-hi_Belebele data_files: - split: queries path: viewer/MLIR-hi/Belebele_test/queries.jsonl - split: corpus path: viewer/MLIR-hi/Belebele_test/corpus.jsonl - config_name: MLIR-hi_MLQA data_files: - split: queries path: viewer/MLIR-hi/MLQA_test/queries.jsonl - split: corpus path: viewer/MLIR-hi/MLQA_test/corpus.jsonl - config_name: MLIR-hi_XQuAD data_files: - split: queries path: viewer/MLIR-hi/XQuAD_test/queries.jsonl - split: corpus path: viewer/MLIR-hi/XQuAD_test/corpus.jsonl - config_name: MMLIR_Belebele data_files: - split: queries path: viewer/MMLIR/Belebele_test/queries.jsonl - split: corpus path: viewer/MMLIR/Belebele_test/corpus.jsonl - config_name: MMLIR_MLQA data_files: - split: queries path: viewer/MMLIR/MLQA_test/queries.jsonl - split: corpus path: viewer/MMLIR/MLQA_test/corpus.jsonl - config_name: MMLIR_MultiEup data_files: - split: queries path: viewer/MMLIR/MultiEup_test/queries.jsonl - split: corpus path: viewer/MMLIR/MultiEup_test/corpus.jsonl - config_name: MMLIR_XQuAD data_files: - split: queries path: viewer/MMLIR/XQuAD_test/queries.jsonl - split: corpus path: viewer/MMLIR/XQuAD_test/corpus.jsonl - config_name: NeuCLIR_NeuCLIR2022 data_files: - split: queries path: viewer/NeuCLIR/NeuCLIR2022_test/queries.jsonl - split: corpus path: viewer/NeuCLIR/NeuCLIR2022_test/corpus.jsonl - config_name: NeuCLIR_NeuCLIR2023 data_files: - split: queries path: viewer/NeuCLIR/NeuCLIR2023_test/queries.jsonl - split: corpus path: viewer/NeuCLIR/NeuCLIR2023_test/corpus.jsonl --- # MLIR Benchmarks Multilingual Information Retrieval (MLIR) evaluation benchmarks used in: - **MIMO: Multilingual Information Retrieval via Monolingual Objectives** (EMNLP 2026) - **SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval** (EMNLP 2026 Findings) Four multilingual QA/retrieval datasets ([Belebele](https://huggingface.co/datasets/facebook/belebele), [MLQA](https://huggingface.co/datasets/facebook/mlqa), [XQuAD-R](https://github.com/google-research-datasets/lareqa), [MultiEuP-v2](https://huggingface.co/datasets/unimelb-nlp/MultiEup-v2)) adapted to the MLIR setting: all language versions of the context passages are pooled into one mixed corpus, and for each query the gold context in **every** language is a positive. ## Layout ``` MLIR-en/ Belebele_test, MLQA_test, XQuAD_test, MultiEup_test # English source queries (SHIFT main results) MLIR-zh/ Belebele_test, MLQA_test, XQuAD_test # Chinese source queries MLIR-vi/ ... # Vietnamese source queries MLIR-hi/ ... # Hindi source queries MMLIR/ Belebele_test, MLQA_test, XQuAD_test, MultiEup_test # queries in ALL languages (MIMO main results) NeuCLIR/ NeuCLIR2022_test, NeuCLIR2023_test # English queries x mixed ru+zh corpus ``` The `NeuCLIR/` tracks follow the NeuCLIRBench MLIR recipe: the per-language [mteb NeuCLIR HardNegatives](https://huggingface.co/datasets/mteb/NeuCLIR2022RetrievalHardNegatives) corpora for Russian and Chinese are pooled (doc ids prefixed `rus::` / `zho::`; Persian excluded), queries are the official English ones from [neuclir/bench](https://huggingface.co/datasets/neuclir/bench), and qrels are the union of the cross-lingual `qrels.rus ∪ qrels.zho`, binarized. The MIMO/SHIFT evaluation code rebuilds these deterministically at runtime; this static copy preserves the exact snapshot used in the papers. Each benchmark directory contains BEIR-style JSONL files: ``` queries.jsonl: {"_id": ..., "text": ...[, "lang": ...]} (MLIR-en/XQuAD uses {qid: text}) corpus.jsonl: {doc_id: {"text": ..., "lang": ...}} qrels.jsonl: {query_id: {doc_id: relevance}} ``` Note: `dt` is the mMARCO language code for Dutch (ISO `nl`). The `viewer/` directory contains record-format mirrors of the same data: `{"_id", "text", "lang"}` rows for queries/corpus (backing the dataset viewer above) and flat `{"query-id", "corpus-id", "score"}` rows for qrels. The evaluation code in the MIMO/SHIFT repositories consumes the raw per-benchmark JSONL files. ## Usage These files are consumed directly by the evaluation code in the [MIMO](https://github.com/yjoonjang/MIMO) and [SHIFT](https://github.com/yjoonjang/SHIFT) repositories (downloaded automatically at evaluation time). Construction scripts are included in both repositories (`scripts/prepare_data/build_benchmarks.py`). ## Citation ```bibtex @inproceedings{jang2026mimo, title = {{MIMO}: Multilingual Information Retrieval via Monolingual Objectives}, author = {Jang, Youngjoon and Hong, Seongtae and Lim, Heuiseok}, booktitle = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing}, year = {2026} } @inproceedings{jang2026shift, title = {{SHIFT}: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval}, author = {Jang, Youngjoon and Hong, Seongtae and Moon, Hyeonseok and Lim, Heuiseok}, booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2026}, year = {2026} } ``` Please also cite the original datasets (Belebele, MLQA, XQuAD/LAReQA, MultiEuP-v2) when using these benchmarks.