| 1 |
Graph Mamba: Towards Learning on Graphs with State Space Models |
提出Graph Mamba以解决图神经网络的长距离依赖问题 |
Mamba SSM state space model |
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| 2 |
Hybrid Inverse Reinforcement Learning |
提出混合逆强化学习以提高样本效率 |
reinforcement learning imitation learning inverse reinforcement learning |
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| 3 |
Rethinking Machine Unlearning for Large Language Models |
提出大语言模型去学习方法以消除不良数据影响 |
reinforcement learning large language model |
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| 4 |
Deep Reinforcement Learning for Controlled Traversing of the Attractor Landscape of Boolean Models in the Context of Cellular Reprogramming |
提出深度强化学习框架以优化细胞重编程策略 |
reinforcement learning deep reinforcement learning |
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| 5 |
World Model on Million-Length Video And Language With Blockwise RingAttention |
提出基于块状环注意力的模型以解决长视频和语言理解问题 |
world model world models |
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| 6 |
Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning |
提出离线多智能体强化学习方案以解决环境不确定性问题 |
reinforcement learning conservative q-learning |
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| 7 |
PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models |
提出PRDP以解决视觉领域大规模奖励微调问题 |
reinforcement learning foundation model |
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| 8 |
Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea |
提出基于时序逻辑的强化学习方法以确保海上交通规则合规性 |
reinforcement learning |
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| 9 |
Disambiguated Node Classification with Graph Neural Networks |
提出一种新方法以解决图神经网络中的模糊节点分类问题 |
representation learning contrastive learning |
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