| Challenge design roadmap |
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4 |
| Chronicling Germany: An Annotated Historical Newspaper Dataset |
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5 |
| Constructing Confidence Intervals for “the” Generalization Error – a Comprehensive Benchmark Study |
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7 |
| Data Acquisition: A New Frontier in Data-centric AI |
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2 |
| Deep Learning for Accurate Diagnosis of Viral Infections through scRNA-seq Analysis: A Comprehensive Benchmark Study |
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1 |
| FlowBench: A Large Scale Benchmark for Flow Simulation over Complex Geometries |
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5 |
| MONSTER: Monash Scalable Time Series Evaluation Repository |
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5 |
| SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning |
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5 |
| Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEs |
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6 |
| Text Quality-Based Pruning for Efficient Training of Language Models |
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3 |
| The FIX Benchmark: Extracting Features Interpretable to eXperts |
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4 |
| Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions |
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0 |
| V-LoL: A Diagnostic Dataset for Visual Logical Learning |
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7 |