17 citations · 19 across the 10 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 +2
Cross-view geo-localization (CVGL) aims to perform visual localization by matching drone-view images with corresponding satellite images. Existing supervised methods rely on large-…
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…
Efficient Mathematical Reasoning Models via Dynamic Pruning and Knowledge Distillation
Fengming Yu, Qingyu Meng, Haiwei Pan +1
With the rapid development of deep learning, large language models have shown strong capabilities in complex reasoning tasks such as mathematical equation solving. However, their s…
UHKD: A Unified Framework for Heterogeneous Knowledge Distillation via Frequency-Domain Representations
Fengming Yu, Haiwei Pan, Kejia Zhang +2
Knowledge distillation (KD) is an effective model compression technique that transfers knowledge from a high-performance teacher to a lightweight student, reducing computational an…
CTS: A Consistency-Based Medical Image Segmentation Model
Kejia Zhang, Lan Zhang, Haiwei Pan +1
In medical image segmentation tasks, diffusion models have shown significant potential. However, mainstream diffusion models suffer from drawbacks such as multiple sampling times a…
MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion
Zhe Li, Haiwei Pan, Kejia Zhang +2
Multi-modality image fusion (MMIF) aims to integrate complementary information from different modalities into a single fused image to represent the imaging scene and facilitate dow…