Saved in:
| Main Authors: | Sheng, Zihao, Huang, Zilin, Chen, Sikai |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.17380 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Found-RL: foundation model-enhanced reinforcement learning for autonomous driving
by: Qu, Yansong, et al.
Published: (2026)
by: Qu, Yansong, et al.
Published: (2026)
Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)
by: Huang, Zilin, et al.
Published: (2024)
HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)
by: Huang, Zilin, et al.
Published: (2024)
Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
by: Remonda, Adrian, et al.
Published: (2021)
by: Remonda, Adrian, et al.
Published: (2021)
VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)
by: Huang, Zilin, et al.
Published: (2024)
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
by: Sukhija, Bhavya, et al.
Published: (2024)
by: Sukhija, Bhavya, et al.
Published: (2024)
Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks
by: Chen, Wenqian, et al.
Published: (2024)
by: Chen, Wenqian, et al.
Published: (2024)
Causal prompting model-based offline reinforcement learning
by: Yu, Xuehui, et al.
Published: (2024)
by: Yu, Xuehui, et al.
Published: (2024)
Scilab-RL: A software framework for efficient reinforcement learning and cognitive modeling research
by: Dohmen, Jan, et al.
Published: (2024)
by: Dohmen, Jan, et al.
Published: (2024)
Deep residual learning with product units
by: Li, Ziyuan, et al.
Published: (2025)
by: Li, Ziyuan, et al.
Published: (2025)
DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving
by: Huang, Zilin, et al.
Published: (2026)
by: Huang, Zilin, et al.
Published: (2026)
Policy-shaped prediction: avoiding distractions in model-based reinforcement learning
by: Hutson, Miles, et al.
Published: (2024)
by: Hutson, Miles, et al.
Published: (2024)
Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model
by: Moen, Hans, et al.
Published: (2024)
by: Moen, Hans, et al.
Published: (2024)
Learning to summarize user information for personalized reinforcement learning from human feedback
by: Nam, Hyunji, et al.
Published: (2025)
by: Nam, Hyunji, et al.
Published: (2025)
SafePLUG: Empowering Multimodal LLMs with Pixel-Level Insight and Temporal Grounding for Traffic Accident Understanding
by: Sheng, Zihao, et al.
Published: (2025)
by: Sheng, Zihao, et al.
Published: (2025)
BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
by: Ikhtiarudin, Azhar, et al.
Published: (2025)
by: Ikhtiarudin, Azhar, et al.
Published: (2025)
Learning When to See for Long-term Traffic Data Collection on Power-constrained Devices
by: Zhang, Ruixuan, et al.
Published: (2024)
by: Zhang, Ruixuan, et al.
Published: (2024)
Guided Safe Shooting: model based reinforcement learning with safety constraints
by: Paolo, Giuseppe, et al.
Published: (2022)
by: Paolo, Giuseppe, et al.
Published: (2022)
Logic-informed reinforcement learning for cross-domain optimization of large-scale cyber-physical systems
by: Wan, Guangxi, et al.
Published: (2025)
by: Wan, Guangxi, et al.
Published: (2025)
Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint
by: Yang, Juntang, et al.
Published: (2025)
by: Yang, Juntang, et al.
Published: (2025)
MetaSSC: Enhancing 3D Semantic Scene Completion for Autonomous Driving through Meta-Learning and Long-sequence Modeling
by: Qu, Yansong, et al.
Published: (2024)
by: Qu, Yansong, et al.
Published: (2024)
Economic span selection of bridge based on deep reinforcement learning
by: Zhang, Leye, et al.
Published: (2024)
by: Zhang, Leye, et al.
Published: (2024)
WEITS: A Wavelet-enhanced residual framework for interpretable time series forecasting
by: Guo, Ziyou, et al.
Published: (2024)
by: Guo, Ziyou, et al.
Published: (2024)
Physics-informed offline reinforcement learning eliminates catastrophic fuel waste in maritime routing
by: Bora, Aniruddha, et al.
Published: (2026)
by: Bora, Aniruddha, et al.
Published: (2026)
Leveraging LLMs for reward function design in reinforcement learning control tasks
by: Cardenoso, Franklin, et al.
Published: (2025)
by: Cardenoso, Franklin, et al.
Published: (2025)
Normalization and effective learning rates in reinforcement learning
by: Lyle, Clare, et al.
Published: (2024)
by: Lyle, Clare, et al.
Published: (2024)
Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
by: Kobayashi, Seijin, et al.
Published: (2025)
by: Kobayashi, Seijin, et al.
Published: (2025)
Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning
by: Zhao, Hanyang, et al.
Published: (2024)
by: Zhao, Hanyang, et al.
Published: (2024)
On the consistency of hyper-parameter selection in value-based deep reinforcement learning
by: Obando-Ceron, Johan, et al.
Published: (2024)
by: Obando-Ceron, Johan, et al.
Published: (2024)
An advantage based policy transfer algorithm for reinforcement learning with measures of transferability
by: Alam, Md Ferdous, et al.
Published: (2023)
by: Alam, Md Ferdous, et al.
Published: (2023)
Optimization of geological carbon storage operations with multimodal latent dynamic model and deep reinforcement learning
by: Wang, Zhongzheng, et al.
Published: (2024)
by: Wang, Zhongzheng, et al.
Published: (2024)
Curriculum reinforcement learning with measurable task representation learning
by: Wen, Yongyan, et al.
Published: (2026)
by: Wen, Yongyan, et al.
Published: (2026)
VLM-SAFE: Vision-Language Model-Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving
by: Qu, Yansong, et al.
Published: (2025)
by: Qu, Yansong, et al.
Published: (2025)
Dynamic feature selection in medical predictive monitoring by reinforcement learning
by: Chen, Yutong, et al.
Published: (2024)
by: Chen, Yutong, et al.
Published: (2024)
CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models
by: Sheng, Zihao, et al.
Published: (2025)
by: Sheng, Zihao, et al.
Published: (2025)
Simulation-based reinforcement learning for real-world autonomous driving
by: Osiński, Błażej, et al.
Published: (2019)
by: Osiński, Błażej, et al.
Published: (2019)
Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
by: Renard, Titouan, et al.
Published: (2024)
by: Renard, Titouan, et al.
Published: (2024)
FlickerFusion: Intra-trajectory Domain Generalizing Multi-Agent RL
by: Koh, Woosung, et al.
Published: (2024)
by: Koh, Woosung, et al.
Published: (2024)
CHARME: A chain-based reinforcement learning approach for the minor embedding problem
by: Ngo, Hoang M., et al.
Published: (2024)
by: Ngo, Hoang M., et al.
Published: (2024)
Chaos-based reinforcement learning with TD3
by: Matsuki, Toshitaka, et al.
Published: (2024)
by: Matsuki, Toshitaka, et al.
Published: (2024)
Similar Items
-
Found-RL: foundation model-enhanced reinforcement learning for autonomous driving
by: Qu, Yansong, et al.
Published: (2026) -
Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024) -
HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024) -
Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
by: Remonda, Adrian, et al.
Published: (2021) -
VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)