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Across three models, two reasoning regimes, and two domains, four findings hold without per-turn reasoning: displaying accurate state is unreliable, an unverified ledger the agent writes itself beats an accurate checklist it is shown, directives help in proportion to the model's obedience, and enforcement needs no obedience but is bounded by the correctness of its state.
SCoRD transforms LLM-based recommendation systems by enabling retrievers to adapt intelligently to user intent without the heavy cost of frequent LLM updates.
Self-attention in recommendation systems overlooks crucial item relations, but PRISM's multi-perspective approach reveals hidden user preferences that boost performance.