What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

Title:What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

Abstract:Agent memory failures are silent: an LLM-based agent can produce a fluent response even when it fails to extract, retain, or retrieve the information needed across sessions. The write-manage-read loop describes the external pipeline of these systems but leaves open which internal computations implement each stage. We trace feature circuits across the Qwen-3 family (0.6B--14B), two memory frameworks (mem0, A-MEM), and a matched Gemma-3 replication, reporting two mechanistic findings plus one deliverable. First, under mem0, control is detectable before content. Routing circuitry is causally active at 0.6B, while content circuitry produces no detectable signal until 4B. Gemma-3 reproduces the same order at 1B and 4B. Small models therefore route memory decisions before they can reliably extract or ground the underlying facts. Second, the shared hub is recruited, not created. Write and Read converge on a late-layer hub that already exists in the base model as a context-grounding substrate, on which memory framing recruits a memory-specific functional direction. The hub and the early routing circuit carry over to A-MEM, indicating that these computations belong to the base model rather than to a particular interface. Building on this circuit structure, we develop an unsupervised stage-level diagnostic that localizes silent failures to the responsible operation at 76.2% accuracy. It outperforms a strong LLM trace judge by 3.1 points as well as a supervised hidden-state probe by 8.8 points. Together, these results establish circuit-level signatures as a practical handle for monitoring agent memory and guiding its structural design.

Artificial Intelligence (cs.AI)

arXiv:2605.03354 [cs.AI]

(or arXiv:2605.03354v3 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2605.03354 Focus to learn more arXiv-issued DOI via DataCite

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