9 papers
A Comprehensive Survey on World Models for Embodied AI
Xinqing Li, Xin He, Le Zhang +3
Embodied AI requires agents that perceive, act, and anticipate how actions reshape future world states. World models serve as internal simulators that capture environment dynamics,…
Unlocking LLM Code Correction with Iterative Feedback Loops
Le Zhang, Suresh Kothari
Large Language Models have shown remarkable capabilities in code generation. However, most existing evaluations focus only on single-attempt accuracy and overlook the iterative ref…
UltraUPConvNet: A UPerNet- and ConvNeXt-Based Multi-Task Network for Ultrasound Tissue Segmentation and Disease Prediction
Zhi Chen, Le Zhang
Ultrasound imaging is widely used in clinical practice due to its cost-effectiveness, mobility, and safety. However, current AI research often treats disease prediction and tissue…
Trustworthy Longitudinal Brain MRI Completion: A Deformation-Based Approach with KAN-Enhanced Diffusion Model
Tianli Tao, Ziyang Wang, Delong Yang +2
Longitudinal brain MRI is essential for lifespan study, yet high attrition rates often lead to missing data, complicating analysis. Deep generative models have been explored, but m…
Grounding Large Language Models as Generalizable Policies in Network Control
Duo Wu, Linjia Kang, Zhimin Wang +9
Designing generalizable control policies that operate reliably under changing conditions is essential for robust network services in modern digital infrastructure. Yet network cont…
ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
Chenchen Zhang, Yuhang Li, Can Xu +17
The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a crit…