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import os |
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import json |
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import datasets |
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import csv |
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_DESCRIPTION = """\ |
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MixBench is a benchmark for evaluating mixed-modality retrieval. It contains queries and corpora from four datasets: MSCOCO, Google_WIT, VisualNews, and OVEN. \ |
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Each subset provides: query, corpus, mixed_corpus, and qrel splits. |
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""" |
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_HOMEPAGE = "https://huggingface.co/datasets/iclr2026-anonymous/MixBench2025" |
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_SUBSETS = ["MSCOCO", "Google_WIT", "VisualNews", "OVEN"] |
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class MixBenchConfig(datasets.BuilderConfig): |
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def __init__(self, name, **kwargs): |
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if name not in _SUBSETS: |
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raise ValueError(f"Unknown subset: {name}. Choose from {_SUBSETS}") |
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super().__init__(name=name, version=datasets.Version("1.0.0"), **kwargs) |
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class MixBench(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [MixBenchConfig(name=subset) for subset in _SUBSETS] |
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def _info(self): |
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features = datasets.Features({ |
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"query_id": datasets.Value("string"), |
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"corpus_id": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"image": datasets.Value("string"), |
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"score": datasets.Value("int32"), |
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}) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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) |
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def _split_generators(self, dl_manager): |
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subset_dir = os.path.join(dl_manager.manual_dir or dl_manager._base_path, self.config.name) |
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return [ |
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datasets.SplitGenerator( |
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name="query", |
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gen_kwargs={"path": os.path.join(subset_dir, "queries.jsonl"), "split": "query"}, |
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), |
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datasets.SplitGenerator( |
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name="corpus", |
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gen_kwargs={"path": os.path.join(subset_dir, "corpus.jsonl"), "split": "corpus"}, |
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), |
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datasets.SplitGenerator( |
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name="mixed_corpus", |
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gen_kwargs={"path": os.path.join(subset_dir, "mixed_corpus.jsonl"), "split": "mixed_corpus"}, |
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), |
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datasets.SplitGenerator( |
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name="qrel", |
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gen_kwargs={"path": os.path.join(subset_dir, "qrels", "qrels.tsv"), "split": "qrel"}, |
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), |
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] |
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def _generate_examples(self, path, split): |
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if split == "qrel": |
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with open(path, encoding="utf-8") as f: |
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reader = csv.DictReader(f, delimiter="\t") |
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for idx, row in enumerate(reader): |
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yield idx, { |
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"query_id": row["query_id"], |
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"corpus_id": row["corpus_id"], |
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"score": int(row["score"]), |
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} |
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else: |
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with open(path, encoding="utf-8") as f: |
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for idx, line in enumerate(f): |
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row = json.loads(line) |
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yield idx, { |
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"query_id": row.get("query_id", ""), |
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"corpus_id": row.get("corpus_id", ""), |
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"text": row.get("text", ""), |
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"image": row.get("image", ""), |
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"score": 0, |
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} |
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