arXiv Artificial Intelligence

C3M: Cross-Session Multimodal Memory Maintenance for Long-Horizon Tasks

C3M: Cross-Session Multimodal Memory Maintenance for Long-Horizon Tasks

Quick summary

arXiv:2609.29735v1 Announce Type: new Abstract: Long-horizon tasks require preserving and later recovering cross-session evidence under a bounded, query-blind memory budget. Existing compression can discard fine-grained visual cues or conflate semantically similar but incompatible observations. We present C3M, a cross-session multimodal memory organization that maintains a bounded active index over persistent source text-image evidence. Relation-aware updates consolidate safe redundancy while preserving complementary and incompatible records. At query time, budgeted routing selects useful inde

Key takeaways

  • arXiv:2609.29735v1 Announce Type: new Abstract: Long-horizon tasks require preserving and later recovering cross-session evidence under a bounded, query-blind memory budget.
  • Existing compression can discard fine-grained visual cues or conflate semantically similar but incompatible observations.
  • We present C3M, a cross-session multimodal memory organization that maintains a bounded active index over persistent source text-image evidence.

Why it matters

This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗