17 citations · 17 across the 6 of their papers we have counts for
10 papers
CoCaRS: Correlation Calibration-Based Redundancy Suppression for Heterogeneous Knowledge Distillation
Fengming Yu, Haiwei Pan, Kejia Zhang +3
Knowledge distillation (KD) enables a compact student model to learn from a powerful teacher and has become an effective paradigm for model compression. The emergence of diverse mo…
STEAM: Stable Self-Training with Elastic Matching and Adaptive Purification
Shaoxiang Wang, Kejia Zhang, Haiwei Pan +1
Cross-view geo-localization (CVGL) aims to achieve GPS-free localization by matching drone-view images with corresponding satellite-view images. Existing supervised methods rely on…
From Foundation to Application: Improving VLA Models in Practice
Wei Wu, Fangjing Wang, Fan Lu +21
Despite recent progress of VLA foundation models, the disparity between laboratory conditions and real-world applications continues to impede their practical implementation. To bri…
A Pragmatic VLA Foundation Model
Wei Wu, Fan Lu, Yunnan Wang +22
Offering great potential in robotic manipulation, a capable Vision-Language-Action (VLA) foundation model is expected to faithfully generalize across tasks and platforms while ensu…
Evolving Excellence: Automated Optimization of LLM-based Agents
Paul Brookes, Vardan Voskanyan, Rafail Giavrimis +18
Agentic AI systems built on large language models (LLMs) offer significant potential for automating complex workflows, from software development to customer support. However, LLM a…
ForgeDAN: An Evolutionary Framework for Jailbreaking Aligned Large Language Models
Siyang Cheng, Gaotian Liu, Rui Mei +7
The rapid adoption of large language models (LLMs) has brought both transformative applications and new security risks, including jailbreak attacks that bypass alignment safeguards…