Beyond the Parameter Monolith: Reconstructive Memories, Executable Skills, and Residual Assembly for Language Models
arXiv cs.AIen
arXiv:2610.04012v1 Announce Type: new Abstract: Language-model systems can separate contextual computation, persistent storage, and exact execution instead of updating all capabilities through one shared parameter system. We investigate FEM-ASM, a finite-element-method-inspired organization in which independently constructed document states and deterministic executable skills contribute typed proposals to a shared language-model state. An explicit residual operator reconciles proposals attached to common interface nodes. We evaluate this organization through controlled experiments and negative results rather than claiming a physical finite-element formulation of language. An attention-free M
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Forskning
Related AI news
- Huawei's Kirin 9050 Pro reveals new logic folding chip designDIGITIMES · October 6, 2026
- Training Numerical Intelligence via Auto-Diagnosis and Skill DiscoveryarXiv cs.AI · October 6, 2026
- CUAWright: A Minimal Unified Interface for Digital AgentsarXiv cs.AI · October 6, 2026
- InvestigationWorlds: An Agentic Environment for Legal InvestigationarXiv cs.AI · October 6, 2026
- Auditing Pairwise Equivalence Judgments: Self-Critique Effects and Diversity Measurement in Multi-Agent Hypothesis GenerationarXiv cs.AI · October 6, 2026
- Agentic Cognitive Depth: Operational Criteria for Evaluating LLM AgentsarXiv cs.AI · October 6, 2026