SSP-Bench: A Hybrid Data Generation Framework for Safety, Security, and Privacy Evaluation
cs.CR, cs.LG, cs.SE
Submitted: 2026-09-21
Updated: 2026-09-26
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- aiXamine: Simplified LLM Safety and Security
- On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
- Stop Uploading Test Data in Plain Text: Practical Strategies for Mitigating Data Contamination by Evaluation Benchmarks
- AutoBencher: Towards Declarative Benchmark Construction
- GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
- Red Teaming Language Models with Language Models
- tinyBenchmarks: evaluating LLMs with fewer examples
- AI and the Everything in the Whole Wide World Benchmark
- TrustLLM: Trustworthiness in Large Language Models
- AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models
- LiveBench: A Challenging, Contamination-Limited LLM Benchmark
- Universal and Transferable Adversarial Attacks on Aligned Language Models
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