151 citations · 606 across the 63 of their papers we have counts for
63 papers
Hide and Seek (HaS): A Lightweight Framework for Prompt Privacy Protection
Yu Chen, Tingxin Li, Huiming Liu +1
Numerous companies have started offering services based on large language models (LLM), such as ChatGPT, which inevitably raises privacy concerns as users' prompts are exposed to t…
Car-Studio: Learning Car Radiance Fields from Single-View and Endless In-the-wild Images
Tianyu Liu, Hao Zhao, Yang Yu +2
Compositional neural scene graph studies have shown that radiance fields can be an efficient tool in an editable autonomous driving simulator. However, previous studies learned wit…
Learning World Models with Identifiable Factorization
Yu-Ren Liu, Biwei Huang, Zhengmao Zhu +4
Extracting a stable and compact representation of the environment is crucial for efficient reinforcement learning in high-dimensional, noisy, and non-stationary environments. Diffe…
NPVForensics: Jointing Non-critical Phonemes and Visemes for Deepfake Detection
Yu Chen, Yang Yu, Rongrong Ni +2
Deepfake technologies empowered by deep learning are rapidly evolving, creating new security concerns for society. Existing multimodal detection methods usually capture audio-visua…
Actively learning a Bayesian matrix fusion model with deep side information
Yangyang Yu, Jordan W. Suchow
High-dimensional deep neural network representations of images and concepts can be aligned to predict human annotations of diverse stimuli. However, such alignment requires the cos…
SplatFlow: Learning Multi-frame Optical Flow via Splatting
Bo Wang, Yifan Zhang, Jian Li +4
The occlusion problem remains a crucial challenge in optical flow estimation (OFE). Despite the recent significant progress brought about by deep learning, most existing deep learn…