Perplexity released a dataset (BrowseSafe)  and benchmark to catch and prevent malicious prompt-injection instructions in real-time. 
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Perplexity released a dataset (BrowseSafe)  and benchmark to catch and prevent malicious prompt-injection instructions in real-time. 
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We trained a prompt injection classifier on BrowseSafe using adaptive-classifier with ModernBERT-base embeddings.
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We trained a prompt injection classifier on BrowseSafe using adaptive-classifier with ModernBERT-base embeddings.
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74.9% F1 on detecting prompt injection in web content.
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74.9% F1 on detecting prompt injection in web content.
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Model -> 
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Model -> 
https://huggingface.co/adaptive-classifier/browsesafe
adaptive-classifier/browsesafe
model
resource
https://huggingface.co/adaptive-classifier/browsesafe
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Dataset -> 
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Dataset -> 
https://huggingface.co/datasets/perplexity-ai/browsesafe-bench
perplexity-ai/browsesafe-bench
dataset
resource
https://huggingface.co/datasets/perplexity-ai/browsesafe-bench
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Repo -> 
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Repo -> 
https://github.com/codelion/adaptive-classifier
https://github.com/codelion/adaptive-classifier
link
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Perplexity released a dataset (BrowseSafe)  and benchmark to catch and prevent malicious prompt-injection instructions in real-time. 

We trained a prompt injection classifier on BrowseSafe using adaptive-classifier with ModernBERT-base embeddings.

74.9% F1 on detecting prompt injection in web content.

Model -> https://huggingface.co/adaptive-classifier/browsesafe 
Dataset -> https://huggingface.co/datasets/perplexity-ai/browsesafe-bench 
Repo -> https://github.com/codelion/adaptive-classifier

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Sundar Shanmuganathan
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