9 citations · 20 across the 7 of their papers we have counts for
8 papers
VisionPsy-Nano: Improving Accuracy, Efficiency, and Reliability in On-Device Vision-Language Models
Khurram Azeem Hashmi, Mohammadreza Zolfaghari, Changdae Park +6
Sub-billion-parameter Vision-Language Models are increasingly viable for on-device deployment, yet compact model size alone does not guarantee usability. On a phone, such a model c…
Sparse Autoencoders as Plug-and-Play Firewalls for Adversarial Attack Detection in VLMs
Hao Wang, Yiqun Sun, Pengfei Wei +2
Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based systems. However, their safety…
C2G2: Controllable Co-speech Gesture Generation with Latent Diffusion Model
Longbin Ji, Pengfei Wei, Yi Ren +3
Co-speech gesture generation is crucial for automatic digital avatar animation. However, existing methods suffer from issues such as unstable training and temporal inconsistency, p…
SR-RKAC: Improving Single Image Defocus Deblurring
Peng Tang, Zhiqiang Xu, Pengfei Wei +5
We propose an efficient deep learning method for single image defocus deblurring (SIDD) by further exploring inverse kernel properties. Although the current inverse kernel method,…
Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis
Ziyue Jiang, Jinglin Liu, Yi Ren +10
Zero-shot text-to-speech (TTS) aims to synthesize voices with unseen speech prompts, which significantly reduces the data and computation requirements for voice cloning by skipping…
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning
Han Zheng, Xufang Luo, Pengfei Wei +3
Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when online interactions are costly. Offline RL provides an alternative so…
Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective
Pengfei Wei, Lingdong Kong, Xinghua Qu +4
Unsupervised video domain adaptation is a practical yet challenging task. In this work, for the first time, we tackle it from a disentanglement view. Our key idea is to handle the…
Language Adaptive Cross-lingual Speech Representation Learning with Sparse Sharing Sub-networks
Yizhou Lu, Mingkun Huang, Xinghua Qu +2
Unsupervised cross-lingual speech representation learning (XLSR) has recently shown promising results in speech recognition by leveraging vast amounts of unlabeled data across mult…