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KeaRepair not only achieves an 83.64% repair rate on C/C++ vulnerabilities but also tackles unique cases that existing methods fail to address.
Adjusting gate sharpness based on routing confidence leads to significant performance gains in Mixture-of-Experts models without the burden of extra parameters.
LLM safety filters can be bypassed by strategically fragmenting and camouflaging malicious intent across multiple turns, achieving a 26% improvement in jailbreak success rate on GPT-5-mini.
