SAMULE: Self-Learning Agents Enhanced by Multi-level Reflection (2025.emnlp-main)
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| Challenge: | Modern AI agents rely on Large Language Models (LLMs) as their reasoning engines, but they still face the challenge of generating meaningful reflections due to inadequate error analysis and a reliance on rare successful trajectories. |
| Approach: | They propose a framework for self-learning agents powered by a retrospective language model that generates reflections during inference. |
| Outcome: | The proposed framework outperforms reflection-based baselines on three challenging benchmarks. |
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