1
Effective Distillation to Hybrid xLSTM Architectures
将知识蒸馏引入混合xLSTM架构，探索高效模型压缩新方向
arXiv:2603.15590v2 Announce Type: replace Abstract: There have been numerous attempts to distill quadratic attention-based large language models (LLMs…
2
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
大模型与小模型协同作战，用混合架构攻克领域任务，兼顾性能与效率。
arXiv:2504.17421v2 Announce Type: replace Abstract: Large language models (LMs) offer broad generalization capabilities but require vast amounts of da…
3
Clay-CNN Hybrids: Leveraging Geo-Foundational Models as Auxiliary Context for Landslide Detection
地理基础模型与CNN混合架构，为滑坡检测提供全新辅助上下文，精度提升显著。
arXiv:2606.14081v1 Announce Type: cross Abstract: Rapid post-event landslide mapping is essential for disaster response but remains difficult to autom…
4
QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction
QuChaTeR 结合量子计算与混沌映射，构建新型混合框架提升地震预测精度，兼具理论创新与实用潜力
arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake …
5
Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning
打破传统荧光标记依赖，多任务学习与混合架构（CNN+Transformer+LLM）让无标记单细胞成像同时完成白细胞分类和蛋白表达预测，为高通量血液分析开辟了低成本、可解释的新路径。
arXiv:2605.14717v1 Announce Type: cross Abstract: Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cyt…