| 1 |
LpWM: A Case for Sparse Representations in World Models |
提出LpWM以解决动态建模中的稠密表示问题 |
world model worldmodel world models |
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| 2 |
ReCoG: Reciprocal Co-Evolution for Multimodal Graph Learning |
提出ReCoG以解决多模态图学习中的结构与语义耦合问题 |
representation learning foundation model multimodal |
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| 3 |
RIBOSPAN: A Long-Context RNA Foundation Model for Versatile RNA Modeling |
提出RIBOSPAN以解决长序列RNA建模问题 |
representation learning foundation model |
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| 4 |
Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs |
提出ADAPT框架以优化后训练大语言模型的蒸馏过程 |
teacher-student distillation large language model |
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| 5 |
MOSH-WM: Mask-Grounded Soft-Hamiltonian Dynamics for Object-Centric World Models |
提出MOSH-WM以解决对象中心世界模型的动态监督问题 |
world model world models |
✅ |
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| 6 |
Interpretable AI with Local Distillation |
提出局部蒸馏方法以提升AI模型的可解释性 |
distillation foundation model |
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| 7 |
Spiking Neural Networks for Continuous Control: Neuromorphic Reinforcement Learning in Conventional Computing |
提出脉冲神经网络以解决连续控制中的强化学习问题 |
reinforcement learning SAC |
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| 8 |
Macro-Action Topological Navigation under Noisy Localization using Reinforcement Learning |
提出基于强化学习的宏观动作拓扑导航以解决噪声定位问题 |
reinforcement learning |
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| 9 |
How to Train a Critic Stably and Efficiently |
提出最佳实践评论优化方法以解决评论训练不稳定问题 |
reinforcement learning large language model |
✅ |
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| 10 |
Graph Representation Learning of Lightweight IoT Ciphers |
提出图表示学习方法以提升轻量级IoT密码的差分分析 |
representation learning |
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| 11 |
FedCC: Towards Addressing Label Distribution Skews in Distillation-Based Federated Learning |
提出FedCC以解决蒸馏基础联邦学习中的标签分布偏斜问题 |
distillation |
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