4 papers
GPU Kernel Optimization Beyond Full Builds: An LLM Framework with Minimal Executable Programs
Ruifan Chu, Anbang Wang, Xiuxiu Bai +2
In high-performance computing, hotspot GPU kernels are primary bottlenecks, and expert manual tuning is costly and hard to port. Large language model methods often assume kernels c…
MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection
Marawan Elbatel, Anbang Wang, Keyuan Liu +6
This paper does not introduce a novel architecture; instead, it revisits a fundamental yet overlooked baseline: adapting human-centric foundation models for anatomical landmark det…
Geometric-Guided Few-Shot Dental Landmark Detection with Human-Centric Foundation Model
Anbang Wang, Marawan Elbatel, Keyuan Liu +4
Accurate detection of anatomic landmarks is essential for assessing alveolar bone and root conditions, thereby optimizing clinical outcomes in orthodontics, periodontics, and impla…
ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models
Anbang Wang, Difei Mei, Zhichao Zhang +9
This paper presents ReverseNER, a method aimed at overcoming the limitation of large language models (LLMs) in zero-shot named entity recognition (NER) tasks, arising from their re…