| --- |
| 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. |
|
|
