3 papers
cs.CL2026
BMAM: Brain-inspired Multi-Agent Memory Framework
Yang Li, Jiaxiang Liu, Yusong Wang +2
Language-model-based agents operating over extended interaction horizons face persistent challenges in preserving temporally grounded information and maintaining behavioral consist…
cs.CV2025
Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
Jiaxiang Liu, Jiawei Du, Xiao Liu +2
Pre-trained vision-language models (VLMs) such as CLIP have demonstrated strong zero-shot capabilities across diverse domains, yet remain highly vulnerable to adversarial perturbat…
cs.CV2025
Modest-Align: Data-Efficient Alignment for Vision-Language Models
Jiaxiang Liu, Yuan Wang, Jiawei Du +3
Cross-modal alignment aims to map heterogeneous modalities into a shared latent space, as exemplified by models like CLIP, which benefit from large-scale image-text pretraining for…