CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models
cs.RO, cs.AI, cs.CV
Submitted: 2025-02-21
Updated: 2025-02-21
DOI: 10.1016/j.trc.2026.105549
Project page: https://zihaosheng.github.io/CurricuVLM
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- GPT-4 Technical Report
- The Llama 3 Herd of Models
- Learning Robust Rewards with Adversarial Inverse Reinforcement Learning
- imitation: Clean Imitation Learning Implementations
- Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving
- VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving
- Reward-Driven Automated Curriculum Learning for Interaction-Aware Self-Driving at Unsignalized Intersections
- Benchmarking Batch Deep Reinforcement Learning Algorithms
- SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards
- Traffic Scene Generation from Natural Language Description for Autonomous Vehicles with Large Language Model
- Proximal Policy Optimization Algorithms
- ScVLM: Enhancing Vision-Language Model for Safety-Critical Event Understanding
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
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