#memory-augmented agents

2 results

cs.AI2026

MemHarness: Memory Is Reconstructed, Not Replayed

Rong Wu, Daocheng Fu, Licheng Wen +10

The paper introduces MemHarness, a framework that lets large language model agents reconstruct and adapt retrieved past experiences to the current context instead of replaying them…

#memory-augmented agents#large language models#experience reconstruction#reinforcement learning

cs.RO2026

Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents

Yixian Zhang, Huanming Zhang, Feng Gao +13

The paper introduces Harness VLA, a memory-augmented framework that combines a frozen vision‑language‑action model with a small set of analytic manipulation primitives to improve r…

#vision-language models#manipulation#memory-augmented agents#task planning