{
  "id": 6534,
  "url": "https://arxiv.org/abs/2603.29953v1",
  "title": "Structured Intent as a Protocol-Like Communication Layer: Cross-Model Robustness, Framework Comparison, and the Weak-Model Compensation Effect",
  "summary": "How reliably can structured intent representations preserve user goals across different AI models, languages, and prompting frameworks? Prior work showed that PPS (Prompt Protocol Specification), a 5W3H-based structured intent framework, improves goal alignment in Chinese and generalizes to English and Japanese. This paper extends that line of inquiry in three directions: cross-model robustness across Claude, GPT-4o, and Gemini 2.5 Pro; controlled comparison with CO-STAR and RISEN; and a user st",
  "authors": "Peng Gang",
  "category": "research",
  "topics": "safety-alignment",
  "orgs": "google",
  "regions": "china,japan",
  "published_at": "2026-03-31T16:20:28.000Z",
  "fetched_at": "2026-07-14T16:32:33.102Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6534",
  "original_url": "https://arxiv.org/abs/2603.29953v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}