Models and dataset used in paper  "The Jailbreak Tax: How Useful Are Your Jailbreak Outputs"
			
	
	AI & ML interests
Security, privacy, and trustworthiness of machine learning systems.
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			Organization Card
		
		The Secure and Private AI (SPY) Lab conducts research on the security, privacy and trustworthiness of machine learning systems. We often approach these problems from an adversarial perspective, by designing attacks that probe the worst-case performance of a system to ultimately understand and improve its safety.
We are based at ETH Zurich. Learn more about our work in our website.
			models
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				ethz-spylab/Llama-3.1-70B-Instruct_refuse_math
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				ethz-spylab/Llama-3.1-70B-Instruct_refuse_biology
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				ethz-spylab/Llama-3.1-8B-Instruct_refuse_bio
		
	
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				ethz-spylab/Llama-3.1-8B-Instruct_refuse_math
		
	
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				ethz-spylab/Llama-3.1-8B-Instruct_do_bio
		
	
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				ethz-spylab/Llama-3.1-8B-Instruct_do_bio_again
		
	
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				ethz-spylab/Llama-3.1-70B-Instruct_do_biology_again_5e-5
		
	
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				ethz-spylab/Llama-3.1-70B-Instruct_do_biology_5e-5
		
	
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				ethz-spylab/Llama-3.1-70B-Instruct_refuse_biology_5e-5
		
	
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				ethz-spylab/Llama-3.1-70B-Instruct_do_math_chat
		
	
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			datasets
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	ethz-spylab/RealMath
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ethz-spylab/stack_exchange_math_bench
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ethz-spylab/math_latex
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ethz-spylab/arxiv_math_bench
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ethz-spylab/EvilMath
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			487
	
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ethz-spylab/ctf-satml24
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ethz-spylab/competition_eval_dataset
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ethz-spylab/competition_trojan1
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ethz-spylab/competition_trojan4
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ethz-spylab/competition_trojan5
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