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Yanna Wang

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#artificial intelligence Preprint Sep 2026

ConvMem: Convolutional Memory for Long-Context Reasoning

ConvMem is a training-free, highly parallelizable framework that reformulates long-context reasoning as a hierarchical convolution, Inspired by CNNs, that outperforms training-free baselines and avoids the risk of overfitting to parametric priors often observed in RL-trained models on out-of-distribution tasks.

Hongming Zhang, Zhao-Zhen Gu, Fengshuo Bai et al. · 0 citations
Preprint Aug 2026

HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation

HyMem is a hierarchical framework that explicitly separates the agent's context into distinct functional layers to separate high-level planning from execution and complex analysis, allowing the model to maintain focus and accuracy across complex, long-horizon tasks.

Xinqi Wang, Jinwei Xiao, Sijia Cui et al. · 1 citation

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