Dimensions overall score 8.0

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• BudgetMem surpasses strong baselines when performance is prioritized in high-budget settings across LoCoMo, LongMemEval, and HotpotQA datasets.result 90%
• BudgetMem delivers better accuracy-cost frontiers under tighter budgets compared to existing approaches.result 85%
• BudgetMem uses a lightweight neural router trained with reinforcement learning to perform budget-tier routing across memory modules.method 90%
• BudgetMem structures memory processing as a set of memory modules, each offered in three budget tiers (Low/Mid/High).method 95%
• The analysis disentangles strengths and weaknesses of different tiering strategies (implementation, reasoning, capacity) for varying budget regimes.result 85%
• Benefits of BudgetMem depend on precise budget-tier strategy alignment with specific application needs, and misalignment could lead to inefficient operations.limitation 80%
• BudgetMem provides runtime agent memory framework for explicit, query-aware performance-cost control, addressing limitations of offline, query-agnostic memory construction.technical 90%
• Prior work on runtime memory utilization often incurs substantial overhead and offers limited explicit control over performance-cost trade-off.technical 80%

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