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README.md
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# Iceberg: Task-Centric Benchmarks for Vector Similarity Search
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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The Iceberg benchmark was presented in the paper [Reveal Hidden Pitfalls and Navigate Next Generation of Vector Similarity Search from Task-Centric Views](https://huggingface.co/papers/2512.12980).
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Iceberg spans 7 diverse datasets across key domains including image classification, face recognition, text retrieval, and recommendation systems. Each dataset contains 1M to 100M vectors enriched with task-specific labels and metrics, enabling evaluation of retrieval algorithms within full application pipelines—not just in isolated recall-speed scenarios. Iceberg benchmarks 13 state-of-the-art VSS algorithms and re-ranks them using task-centric performance metrics, uncovering substantial deviations from conventional recall/speed-based rankings. Morever, Iceberg propose an interpretable decision tree to guide practitioners in selecting and tuning VSS methods for specific workloads.
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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## Datasets
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## Pipeline
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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## Results
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### Iceberg LeaderBoard 1.0
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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### Task-centric performance versus two similarity metrics
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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### Query Performance on Synthetic Recall@100
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/
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</div>
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## Citation
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# Iceberg: Task-Centric Benchmarks for Vector Similarity Search
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/logo.png" width="210px">
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</div>
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The Iceberg benchmark was presented in the paper [Reveal Hidden Pitfalls and Navigate Next Generation of Vector Similarity Search from Task-Centric Views](https://huggingface.co/papers/2512.12980).
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Iceberg spans 7 diverse datasets across key domains including image classification, face recognition, text retrieval, and recommendation systems. Each dataset contains 1M to 100M vectors enriched with task-specific labels and metrics, enabling evaluation of retrieval algorithms within full application pipelines—not just in isolated recall-speed scenarios. Iceberg benchmarks 13 state-of-the-art VSS algorithms and re-ranks them using task-centric performance metrics, uncovering substantial deviations from conventional recall/speed-based rankings. Morever, Iceberg propose an interpretable decision tree to guide practitioners in selecting and tuning VSS methods for specific workloads.
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/main.png" width="900px">
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</div>
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## Datasets
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## Pipeline
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/pipeline.png" width="900px">
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</div>
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## Results
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### Iceberg LeaderBoard 1.0
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/leaderboard.png" width="900px">
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</div>
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### Task-centric performance versus two similarity metrics
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/ImageNet-EVA02_metric.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/ImageNet-ConvNeXt_metric.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/Glink360K-IR101_metric.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/BookCorpus_metric.png" width="900px">
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</div>
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### Query Performance on Synthetic Recall@100
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/ImageNet-DINOv2.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/Glink360k-IR101.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/BookCorpus.png" width="900px">
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</div>
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<div align=center>
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<img src="https://github.com/ZJU-DAILY/Iceberg/raw/main/pictures/sigmod26/Commerce.png" width="900px">
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</div>
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## Citation
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