Tag: Large Language Model
All the articles with the tag "Large Language Model".
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本文提出自推理语言模型(SRLM),通过少量推理催化数据引导模型自生成更长推理链并迭代自训练,在多个推理基准上实现平均 +2.5 个百分点的性能提升,展现了探索深度和创造性推理路径的潜力。
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Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space
本文提出 LATENTSEEK 框架,通过在潜在空间中基于策略梯度的测试时实例级适应(TTIA),显著提升大型语言模型的推理能力,同时探索测试时扩展的新方向。
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Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
本文提出了一种动态整合框架,通过自适应选择网络和动态加权融合策略从多个LLM中聚合知识,显著提升性能并减少50%的知识干扰,同时保持计算效率。
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Local Mixtures of Experts: Essentially Free Test-Time Training via Model Merging
本文提出测试时模型合并(TTMM)方法,通过在训练时预训练大量专家模型并在测试时动态合并参数,以几乎无测试时开销的方式逼近测试时训练(TTT)的语言建模性能。
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Multilingual Performance of a Multimodal Artificial Intelligence System on Multisubject Physics Concept Inventories
This exploratory study evaluates GPT-4o's multilingual and multimodal performance on physics concept inventories, revealing strong results in English and text-based tasks but significant weaknesses in visual interpretation and non-Western languages, highlighting implications for equitable AI integration in education.