19 citations · 34 across the 10 of their papers we have counts for
4 papers · 1 filter
Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
Jiajun Fan, Shuaike Shen, Chaoran Cheng +3
Recent advancements in reinforcement learning (RL) have achieved great success in fine-tuning diffusion-based generative models. However, fine-tuning continuous flow-based generati…
Planning Under Observation Mismatch for Traffic Signal Control via Adaptive Modular World Models
Zherui Huang, Yicheng Liu, Chumeng Liang +1
Deploying learned decision-making systems often requires transferring to new sites where the sensing pipeline differs. In such cases, observations can change in semantics and dimen…
Real-World Benchmarks Make Membership Inference Attacks Fail on Diffusion Models
Chumeng Liang, Jiaxuan You
Membership inference attacks (MIAs) on diffusion models have emerged as potential evidence of unauthorized data usage in training pre-trained diffusion models. These attacks aim to…
FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
Zhanyu Liu, Chumeng Liang, Guanjie Zheng +1
This paper proposes the fine-grained traffic prediction task (e.g. interval between data points is 1 minute), which is essential to traffic-related downstream applications. Under t…