Persistent Memory and Iterative Improvement in an LLM Agent for Chinese-Character Drawing
Does persistent memory accumulated from previous attempts help an LLM agent solve new problems, and does memory design affect that benefit?
ProofPaper ↗
Key points
- We study programmatic Chinese-character drawing across five agent conditions attempting the same 668 items.
- Accumulated memory produces modest aggregate gains despite substantial growth in the memory stores: free-form notes improve first-attempt success by 4.6 percentage points, while a design combining free-form memory with reusable code improves it by 2.8 points.
- A separate post-hoc comparison finds a much larger improvement when the code-bank agent receives privileged, target-specific structural supervision.
- These results suggest that memory design may affect where accumulated experience becomes useful, even when its average benefit is modest.
Sources (1)
- [1]Persistent Memory and Iterative Improvement in an LLM Agent for Chinese-Character DrawingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 06:20 PM
Does persistent memory accumulated from previous attempts help an LLM agent solve new problems, and does memory design affect that benefit?
We study programmatic Chinese-character drawing across five agent conditions attempting the same 668 items.
Extractive summary: sentences quoted from the sources.
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