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Short answer

Memory is what lets an agent improve across long interactions. A 2024 survey reviews how memory modules are designed and evaluated. A 2026 benchmark, DyadMem, adds memory about how an agent should work with a specific user, and finds that models answer well when given the right memory but drop sharply when they must capture, update and recall it themselves. [S1][S2]

Practical takeaways

• Test the full pipeline (capture, update, recall), not just final-answer QA. [S2]
• Watch for low capture recall and unsafe deletions. [S2]

Claims

• id: C1 claim: Memory supports agent-environment interactions. source: S1 evidence: "The key component to support agent-environment interactions is the memory of the agents."
• id: C2 claim: The survey reviews how to design and evaluate the memory module. source: S1 evidence: "we systematically review previous studies on how to design and evaluate the memory module."
• id: C3 claim: Gold-Memory QA is strong but Full-Pipeline QA drops sharply. source: S2 evidence: "Gold-Memory QA is consistently strong, yet Full-Pipeline QA drops sharply."
• id: C4 claim: Results reveal low capture recall and unsafe-deletion issues. source: S2 evidence: "reveal low Capture recall, incomplete Recall, and unsafe-deletion issues"

Sources

• [S1] [2404.13501] A Survey on the Memory Mechanism of Large Language Model based Agents. arXiv. https://arxiv.org/abs/2404.13501 . License: CC BY 4.0. Accessed 2026-11-04.
• [S2] [2610.03020] DyadMem: A Long-Term Memory Benchmark of How Agents Work with Users. arXiv. https://arxiv.org/abs/2610.03020 . License: CC BY 4.0. Accessed 2026-11-04.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted).

@misc{iil_note_z562xx3f,
  author = {{iinventedlight}},
  title = {{How LLM agent memory is designed and evaluated}},
  howpublished = {iinventedlight Library},
  year = {2026},
  date = {2026-11-04},
  url = {https://iinventedlight.com/library/notes/ao-memory-mechanisms-survey/},
  note = {Permanent ID iil:note:z562xx3f. License: CC-BY-4.0.},
}

Markdown

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