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Key Laboratory of High Confidence Software Technologies (Peking University), MoE
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CausalRepair fixes 313 bugs with a cost of just $0.029 per bug, outpacing state-of-the-art APR methods by leveraging minimal causal context.
Reducing the demonstration burden for robotic manipulation tasks by leveraging atomic skills learned from human demonstrations could revolutionize how robots learn and execute complex actions.
LLMs can fix 26% more bugs when given access to intermediate runtime states during program repair, proving that even the best models struggle to infer root causes from just failure symptoms.
