11 citations · 14 across the 13 of their papers we have counts for
13 papers
No Prompt, No Leaks: A Robust Generative Steganography Framework via Prompt-Free Diffusion
Jingwen Cai, Fen Xiao, Shuhua Deng +1
Generative image steganography synthesizes stego images directly from secret information to achieve inherent security advantages. Latent Diffusion Models (LDMs) have recently emerg…
Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization
Jia Zhang, Tengfei Ma, Tianle Li +3
Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly constrain downstream outcomes. Ex…
Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints
Songping Peng, Zhiheng Zhang, Daojian Zeng +2
Safety alignment in Large Language Models (LLMs) remains highly fragile during fine-tuning, where even benign adaptation can degrade pre-trained refusal behaviors and enable harmfu…
SAHMM-VAE: A Source-Wise Adaptive Hidden Markov Prior Variational Autoencoder for Unsupervised Blind Source Separation
Yuan-Hao Wei
We propose SAHMM-VAE, a source-wise adaptive Hidden Markov prior variational autoencoder for unsupervised blind source separation. Instead of treating the latent prior as a single…
Supervised Fine Tuning of Large Language Models for Domain Specific Knowledge Graph Construction:A Case Study on Hunan's Historical Celebrities
Junjie Hao, Chun Wang, Ying Qiao +4
Large language models and knowledge graphs offer strong potential for advancing research on historical culture by supporting the extraction, analysis, and interpretation of cultura…
Distilling Knowledge from Heterogeneous Architectures for Semantic Segmentation
Yanglin Huang, Kai Hu, Yuan Zhang +2
Current knowledge distillation (KD) methods for semantic segmentation focus on guiding the student to imitate the teacher's knowledge within homogeneous architectures. However, the…
DiffCL: A Diffusion-Based Contrastive Learning Framework with Semantic Alignment for Multimodal Recommendations
Qiya Song, Jiajun Hu, Lin Xiao +3
Multimodal recommendation systems integrate diverse multimodal information into the feature representations of both items and users, thereby enabling a more comprehensive modeling…
Explicit Relational Reasoning Network for Scene Text Detection
Yuchen Su, Zhineng Chen, Yongkun Du +4
Connected component (CC) is a proper text shape representation that aligns with human reading intuition. However, CC-based text detection methods have recently faced a developmenta…
Multimodal Graph Neural Network for Recommendation with Dynamic De-redundancy and Modality-Guided Feature De-noisy
Feng Mo, Lin Xiao, Qiya Song +2
Graph neural networks (GNNs) have become crucial in multimodal recommendation tasks because of their powerful ability to capture complex relationships between neighboring nodes. Ho…
Out of Length Text Recognition with Sub-String Matching
Yongkun Du, Zhineng Chen, Caiyan Jia +2
Scene Text Recognition (STR) methods have demonstrated robust performance in word-level text recognition. However, in real applications the text image is sometimes long due to dete…
Learning to Rank Patches for Unbiased Image Redundancy Reduction
Yang Luo, Zhineng Chen, Peng Zhou +3
Images suffer from heavy spatial redundancy because pixels in neighboring regions are spatially correlated. Existing approaches strive to overcome this limitation by reducing less…
Self-distillation Augmented Masked Autoencoders for Histopathological Image Classification
Yang Luo, Zhineng Chen, Shengtian Zhou +1
Self-supervised learning (SSL) has drawn increasing attention in histopathological image analysis in recent years. Compared to contrastive learning which is troubled with the false…
MSDNN: Multi-Scale Deep Neural Network for Salient Object Detection
Fen Xiao, Wenzheng Deng, Liangchan Peng +3
Salient object detection is a fundamental problem and has been received a great deal of attentions in computer vision. Recently deep learning model became a powerful tool for image…