Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Prediction

no code implementations • 9 Oct 2023 • Yujie Ding, Shuai Jia, Tianyi Ma, Bingcheng Mao, Xiuze Zhou, Liuliu Li, Dongming Han

However, integrating LLMs into existing quantitative models presents two primary challenges: the insufficient utilization of semantic information embedded within LLMs and the difficulties in aligning the latent information within LLMs with pre-existing quantitative stock features.

Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition

no code implementations • 13 Oct 2022 • Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen, Xiaokang Yang, Chao Ma

For face recognition attacks, existing methods typically generate the l_p-norm perturbations on pixels, however, resulting in low attack transferability and high vulnerability to denoising defense models.

Adversarial Attack Attribute +2

Exploring Frequency Adversarial Attacks for Face Forgery Detection

no code implementations • CVPR 2022 • Shuai Jia, Chao Ma, Taiping Yao, Bangjie Yin, Shouhong Ding, Xiaokang Yang

In addition, the proposed frequency attack enhances the transferability across face forgery detectors as black-box attacks.

Adversarial Attack Meta-Learning

IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking

1 code implementation • CVPR 2021 • Shuai Jia, Yibing Song, Chao Ma, Xiaokang Yang

Recently, adversarial attack has been applied to visual object tracking to evaluate the robustness of deep trackers.

Adversarial Attack Image Classification +3

Robust Tracking against Adversarial Attacks

2 code implementations • ECCV 2020 • Shuai Jia, Chao Ma, Yibing Song, Xiaokang Yang

On one hand, we add the temporal perturbations into the original video sequences as adversarial examples to greatly degrade the tracking performance.

Adversarial Attack