Xiaodong Lu

CoKL enables LLMs to learn new tasks without sacrificing previously acquired capabilities, striking a balance that traditional methods fail to achieve.

Overcome the prohibitive cost of ground-truth labels in reinforcement learning by actively acquiring labels for only the most valuable samples, leading to stable training and improved performance even with limited annotation budgets.