AI agents can trust stale memory over fresh evidence, and bigger models do not reliably fix this.

Persistent memory can make an agent confidently wrong even when current evidence is available, so stale facts should be resolved before they reach the model.

The paper tests Qwen3 models from 0.6B to 8B on tasks where stored memory is outdated.

When memory is needed, they follow the stale value 92%–100% of the time.

And making an old note look newer can fool larger models even more.

Their fix depends on model size.

For 4B and 8B models, timestamps and source metadata are enough to recover most accuracy.

The 0.6B and 1.7B models need the stale conflict resolved before they see it.

So the paper suggests: treat agent memory as untrusted input.