Tag: Adaptive Systems
All the articles with the tag "Adaptive Systems".
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ThinkSwitcher: When to Think Hard, When to Think Fast
ThinkSwitcher通过一个轻量级自适应框架,使单一大型推理模型根据任务复杂性动态切换长短链式推理模式,在数学推理基准上减少20-30%计算成本,同时在复杂任务上保持较高准确率。
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Learn to Reason Efficiently with Adaptive Length-based Reward Shaping
本文通过提出基于强化学习的LASER系列方法(LASER, LASER-D, LASER-DE),利用动态和难度感知的长度奖励塑造,在保持大型推理模型性能的同时显著提高token效率,在多个数学推理基准上实现了Pareto最优的准确率和效率权衡。
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AdaptMI: Adaptive Skill-based In-context Math Instruction for Small Language Models
本文提出AdaptMI和AdaptMI+自适应方法,通过基于奖励模型检测问题难度并针对困难问题选择技能-based in-context示例,提高小语言模型在数学推理任务中的性能,同时避免认知过载。
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LLM-Independent Adaptive RAG: Let the Question Speak for Itself
This paper introduces LLM-independent adaptive retrieval using 27 external information features across 7 groups, achieving comparable QA performance to LLM-based methods on 6 datasets while significantly improving efficiency by eliminating additional LLM calls during inference.
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Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
本文提出PLAN-AND-ACT框架,通过分离规划和执行模块、利用合成数据训练和动态重规划,提高LLM代理在复杂长期任务中的性能,并在web导航基准上达到state-of-the-art结果。