| 1 |
world2vec: Mechanistic world models through latent dynamics learning |
提出world2vec以实现机械世界模型的学习 |
world model world models dreamer |
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| 2 |
DYNAS: A Dynamic Network Penetration Testing Framework Using Deep Hierarchical Reinforcement Learning |
提出DYNAS框架以解决动态网络渗透测试问题 |
reinforcement learning penetration |
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| 3 |
H$^2$R: Hierarchical Hint-Based Reward for Mathematical Reasoning via Reinforcement Learning |
提出层次提示奖励以解决复杂数学推理问题 |
reinforcement learning reward design large language model |
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| 4 |
Training Foundation Models with a Single Algorithm |
提出统一训练算法以简化基础模型训练过程 |
reinforcement learning foundation model |
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| 5 |
Reinforcement Learning Under Runtime Confounding: Policy Learning and Off-Policy Evaluation |
提出强化学习算法以解决运行时混淆问题 |
reinforcement learning policy learning |
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| 6 |
From MS/MS evidence to adaptive spectroscopic characterization: Reinforcement learning guided by candidate molecular structures |
提出结构信息驱动的深度Q网络以优化小分子鉴定 |
reinforcement learning multimodal |
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| 7 |
Reinforcement learning for control of partial differential equations |
提出强化学习方法以控制偏微分方程系统 |
reinforcement learning |
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| 8 |
SCARL: Sequence Confidence-Aligned Reinforcement Learning |
提出SCARL以解决序列信心对齐的强化学习问题 |
reinforcement learning |
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| 9 |
Latent Prediction Yields Cross-Subject Alignable Representations in Sensory-Evoked fMRI |
提出自监督学习方法以实现跨参与者fMRI数据对齐 |
JEPA Joint-Embedding Predictive Architecture joint-embedding predictive architecture |
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| 10 |
Confidence-Aware Speed-over-Ground Estimation from Doppler Spectra via Reconstruction-Based Representation Learning |
提出基于重建学习的信心感知地面速度估计方法 |
representation learning |
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| 11 |
Escaping Path Mirages in Offline Goal-Conditioned Reinforcement Learning |
提出分支感知图规划以解决离线目标条件强化学习中的路径幻影问题 |
reinforcement learning |
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| 12 |
Turing LLM Post-Training: Calibrated Distillation and Efficient Dynamic-MoE Execution |
提出动态路由混合专家模型的后训练方法以提升整合效率 |
distillation |
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| 13 |
LinQuant: Functional Invariances for Low-Precision Linear Recurrences |
提出LinQuant框架以解决低精度线性递归推理问题 |
Mamba large language model |
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| 14 |
Safe Multi-Objective Reinforcement Learning: Zero Constraint Violation and Primal-Averaging Convergence |
提出安全多目标强化学习算法以解决约束违反问题 |
reinforcement learning |
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| 15 |
IMRouter: Imbalance-aware Temporal Pattern Routing for LLM-based Time Series Forecasting |
提出IMRouter以解决时间序列预测中的模式不平衡问题 |
representation learning large language model |
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| 16 |
Grounding Predictive Reliability through Masked Observability |
提出MORSE以解决预测不确定性语义模糊问题 |
representation learning PULSE |
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| 17 |
Improving the Intrinsic Interpretability of Differentiable Decision Trees through Euclidean Feature-Concentration Regularisation |
提出欧几里得集中可微决策树以提升特征解释性 |
reinforcement learning PPO |
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| 18 |
Density-Guided Bootstrap Boundaries for Latent World-Model Reinforcement Learning |
提出密度引导的自举边界以解决模型依赖深度选择问题 |
reinforcement learning world model world models |
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| 19 |
CAMEL: Cross-Architecture Masked Embedding Learning for Ultra-Lightweight Retinal Foundation Models |
提出CAMEL以解决轻量级视网膜模型的计算复杂性问题 |
representation learning distillation foundation model |
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| 20 |
On the Origin and Evolution of Training-Inference Mismatch in LLM Reinforcement Learning |
提出差异-滞后校正方法以解决LLM强化学习中的训练推理不匹配问题 |
reinforcement learning large language model |
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| 21 |
Communication-Efficient Private Federated Reinforcement Learning with Post-Quantum Authentication for Vehicular Networks |
提出一种通信高效的私有联邦强化学习方法以解决车载网络中的数据隐私问题 |
reinforcement learning |
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| 22 |
Meshless Latent Dynamics Models for Model Order Reduction of time-dependent Partial Differential Equations |
提出无网格潜在动力学模型以解决时间相关偏微分方程的模型降阶问题 |
latent dynamics |
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| 23 |
Turing LLM Post-Training: Calibrated Distillation and Efficient Dynamic-MoE Execution |
提出动态路由专家模型的后训练方法以提高整合效率 |
distillation |
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| 24 |
Bayesian Distribution System State Estimation with Flow Matching |
提出PoSE以解决配电系统状态估计中的不确定性问题 |
flow matching |
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| 25 |
Steering Vectors as a Training Signal in LLM Post-Training |
提出使用引导向量作为LLM后训练信号以提升性能 |
reinforcement learning distillation |
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| 26 |
TensorSSM: Memorizing Spatial Position in Dynamic State Space for Tensor Core Generation |
提出TensorSSM以解决高维张量存储效率问题 |
SSM state space model |
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