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Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory

46 upvotes · 7 AUG 2026 · Taeil Kim, Kangsan Kim, Sung Ju Hwang

This paper introduces Agent Memory Distillation, a technique that allows small language models to learn from a larger teacher model by transferring structured knowledge through hierarchical memory. Practitioners might care about this approach because it could improve the performance of small language models in tasks that require complex decision-making.

continual learninghierarchical memorylanguage modelsteacher-student modelsmemory-based methods