Meta-TTL: Meta-Learning Self-Improvement Policies for Language Agents
Meta-TTL is introduced, a framework that formulates the discovery of effective self-improvement policies as a bi-level optimization problem and consistently outperforms existing baselines, suggesting that the optimized self-improvement policy encodes transferable meta-strategies that generalize beyond the training task...
Z. Lou, Hui Chen, Yi-Bo Li et al.
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