3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in context-specific-spam-detection-4
Use these libraries to find context-specific-spam-detection-4 models and implementations
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The impact of this imbalance on spam training data sets is investigated and it is shown that simple Bag-of-Words models are best with extreme imbalance, but a neural model that fine-tunes using language models from other domains significantly improves the F1 score, but not to the levels of domain-specific neural models.
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