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Nanjing University of Posts and Telecommunications
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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.
Recursive composition of verifiable environments can boost reasoning performance in RL by up to 3.1 points while using only a fraction of the original environments.
LLMs, when orchestrated as collaborative agents, can dramatically improve vulnerability-inducing commit identification, outperforming existing SZZ algorithms by a large margin.
