新闻
SUMONE: A Simple and Efficient Summarizer for Plug-and-Play Agent Memory
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- SUMONE is a summarizer that compresses agent interaction histories using masked reconstruction, reducing inference costs by 75-78% without task-specific training.
- 为何重要
- Engineers building long-horizon language model agents need efficient context management to handle growing interaction histories without retraining for each task.
- 注意
- The paper shows performance drops of 0.04 on benchmarks; real-world impact on agent quality across diverse downstream tasks remains unclear.
- agent
- long-horizon
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