7 citations · 7 across the 14 of their papers we have counts for
8 papers · 1 filter
BioMedVR: Confusion-Aware Mixture-of-Prompt Experts for Biomedical Visual Reprogramming
Jiaxiang Liu, Tianxiang Hu, Juwei Guan +5
Recent advances in vision-language models (VLMs) such as CLIP have demonstrated strong generalization across natural-image domains. However, adapting these models to biomedical ima…
Toward Signing Activity Projection in Sign Language Interaction
Takao Obi, Wang Yusong, Koji Inoue +1
Social robots must interact robustly not only with users assumed by speech-centered systems but also with diverse users whose communication relies on different modalities, e.g., si…
ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs
Ailiang Lin, Zhuoyun Li, Yusong Wang +3
Recent advances in Large Language Models (LLMs) have opened new avenues for generating training-free text embeddings. However, the causal attention in decoder-only LLMs prevents ea…
Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models
Xiao Liu, Jiaxiang Liu, Boci Peng +6
Vision Language Models adapt well to downstream tasks but are highly vulnerable to adversarial perturbations that disrupt cross-modal semantic alignment. Existing defenses are larg…
Exposing and Mitigating Temporal Attack in Deepfake Video Detection
Zheyuan Gu, Minghao Shao, Zhen Wang +4
While spatiotemporal deepfake detectors achieve high AUC, our experiments reveal their susceptibility to evasion attacks. These models tend to overfit on fragile temporal spectrum…
Emotion Recognition in Sign Language Conversation
Yusong Wang, Keyu Mao, Takao Obi +2
Emotion Recognition in Conversation is a core component of affective computing, while current sign language emotion datasets primarily focus on isolated sentences and lack conversa…
ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework
Yusong Wang, Chuang Yang, Jiawei Wang +5
Human mobility generation aims to synthesize plausible trajectory data, which is widely used in urban system research. While Large Language Model-based methods excel at generating…
MMPG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning
Yusong Wang, Jialun Shen, Zhihao Wu +6
Graph Neural Networks (GNNs) have been widely adopted for Protein Representation Learning (PRL), as residue interaction networks can be naturally represented as graphs. Current GNN…