Lightweight LLM Agent Memory with Small Language Models (2026 · 6 citations)
LLM agents need persistent memory to stay consistent across long, multi-turn interactions. Existing approaches force a choice: similarity-search memory is fast but its accuracy varies, while memory managed through repeated large-model calls is more accurate but adds latency at every turn. LightMem addresses this by…
Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models (2026)
Reasoning quality in LLMs depends heavily on hand-written prompts and decoding settings. Small rewordings or configuration changes can cause large accuracy swings, and earlier automatic prompt optimizers usually run a single-agent local search that adjusts only the prompt. Agent-GWO addresses this by treating each…

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Updated 1 November 2026