2 citations · 4 across the 7 of their papers we have counts for
7 papers
Individual Control Barrier Functions-Guided Diffusion Model for Safe Offline Multi-Agent Reinforcement Learning
Qingyun Guo, Junyi Shi, Jianuo Huang +1
Offline reinforcement learning allows control policies to be learned directly from data without online interaction, making it suitable for safety-critical tasks. Recent studies hav…
CloneShield: A Framework for Universal Perturbation Against Zero-Shot Voice Cloning
Renyuan Li, Zhibo Liang, Haichuan Zhang +5
Recent breakthroughs in text-to-speech (TTS) voice cloning have raised serious privacy concerns, allowing highly accurate vocal identity replication from just a few seconds of refe…
Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information
Yauwai Yim, Chunkit Chan, Tianyu Shi +4
Large language models (LLMs) have shown success in handling simple games with imperfect information and enabling multi-agent coordination, but their ability to facilitate practical…
SECRM-2D: RL-Based Efficient and Comfortable Route-Following Autonomous Driving with Analytic Safety Guarantees
Tianyu Shi, Ilia Smirnov, Omar ElSamadisy +1
Over the last decade, there has been increasing interest in autonomous driving systems. Reinforcement Learning (RL) shows great promise for training autonomous driving controllers,…
TSDiT: Traffic Scene Diffusion Models With Transformers
Chen Yang, Tianyu Shi
In this paper, we introduce a novel approach to trajectory generation for autonomous driving, combining the strengths of Diffusion models and Transformers. First, we use the histor…
WcDT: World-centric Diffusion Transformer for Traffic Scene Generation
Chen Yang, Yangfan He, Aaron Xuxiang Tian +5
In this paper, we introduce a novel approach for autonomous driving trajectory generation by harnessing the complementary strengths of diffusion probabilistic models (a.k.a., diffu…
A Fully Data-Driven Approach for Realistic Traffic Signal Control Using Offline Reinforcement Learning
Jianxiong Li, Shichao Lin, Tianyu Shi +5
The optimization of traffic signal control (TSC) is critical for an efficient transportation system. In recent years, reinforcement learning (RL) techniques have emerged as a popul…