Echelon: Auditable Aggregate-Only Language-Model Adaptation Across Privacy Boundaries
Cross-organization language-model adaptation increasingly faces hard governance constraints: in many deployments, device-level model state-parameters, activations, optimizer state, and per-device updates-cannot be exported outside an administrative boundary. Existing distributed and federated stacks typically assume cross-site model exchange and then retrofit privacy mechanisms, which complicates compliance and makes auditing brittle. We present Echelon, a boundary-first training architecture th
Record details
Published: 1 June 2026
Source: arXiv
Category: Research
Topics: Regulation · Privacy · Transparency
Retrieved: 14 July 2026
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ethics.ai (1 June 2026), “Echelon: Auditable Aggregate-Only Language-Model Adaptation Across Privacy Boundaries,” evidence record 3259, https://ethics.ai/record/3259 (originally published by arXiv).
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