{
  "video_id": "2606.04823",
  "channel": "cs.AI",
  "title": "R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search",
  "scores": {
    "depth": 3,
    "novelty": 3,
    "aria_relevance": 3,
    "production_ready": 2
  },
  "avg_score": 2.75,
  "verdict": "promote",
  "one_line_reason": "Novel multi-axis reasoning decomposition for agentic LLM reliability with rigorous eval on constrained design; directly addresses Aria's agent-architecture, memory-invalidation, and cost-optimization (4B vs 70B parity).",
  "model": "claude-haiku-4-5-20251001",
  "cost_usd": 0.001832,
  "triaged_at": "2026-06-04T15:00:56.065406+00:00"
}