1 citations · 1 across the 10 of their papers we have counts for
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GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving
Yingzi Ma, Chaowei Xiao, Ming Jiang
Vision-language models (VLMs) for autonomous driving have shown promising performance, but their ability to handle region-specific traffic rules remains underexplored, raising unce…
SafeGen-Bench: Benchmarking Safety in Image-Conditioned Text-to-Video Generation
Yingzi Ma, Xiaogeng Liu, Yawen Zheng +1
With the rapid advancements in text-to-image diffusion models, generative video models (T2V models) like Sora can now produce short synthetic videos from a text prompt or an initia…
dVLM-AD: Enhance Diffusion Vision-Language-Model for Driving via Controllable Reasoning
Yingzi Ma, Yulong Cao, Wenhao Ding +6
The autonomous driving community is increasingly focused on addressing the challenges posed by out-of-distribution (OOD) driving scenarios. A dominant research trend seeks to enhan…
Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Yingzi Ma, Jiongxiao Wang, Fei Wang +10
Machine unlearning has emerged as an effective strategy for forgetting specific information in the training data. However, with the increasing integration of visual data, privacy c…
Dolphins: Multimodal Language Model for Driving
Yingzi Ma, Yulong Cao, Jiachen Sun +2
The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world scenarios with human-like understanding and responsiveness. In this paper, we introduce Dolph…