4 citations · 7 across the 9 of their papers we have counts for
10 papers
What Should a Skill Remember? Quality--Cost Trade-offs in Cost-Aware Skill Rewriting for Language Model Agents
Qinghua Xing, Yinda Chen, Yaping Jin +6
Large language model agents increasingly rely on skills: reusable procedural documents encoding workflows, tool use, implementation patterns, validation checks, and domain rules. S…
Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation
Jinpeng Lu, Linghan Cai, Yinda Chen +4
Lightweight 3D medical image segmentation remains constrained by a fundamental \textit{``efficiency / robustness conflict''}, particularly when processing complex anatomical struct…
Does DINOv3 Set a New Medical Vision Standard? Benchmarking 2D and 3D Classification, Segmentation, and Registration
Che Liu, Yinda Chen, Haoyuan Shi +21
The advent of large-scale vision foundation models, pre-trained on diverse natural images, has marked a paradigm shift in computer vision. However, how the frontier vision foundati…
Dual form Complementary Masking for Domain-Adaptive Image Segmentation
Jiawen Wang, Yinda Chen, Xiaoyu Liu +4
Recent works have correlated Masked Image Modeling (MIM) with consistency regularization in Unsupervised Domain Adaptation (UDA). However, they merely treat masking as a special fo…
QMamba: Post-Training Quantization for Vision State Space Models
Yinglong Li, Xiaoyu Liu, Jiacheng Li +3
State Space Models (SSMs), as key components of Mamaba, have gained increasing attention for vision models recently, thanks to their efficient long sequence modeling capability. Gi…
Multi-Granularity Semantic Revision for Large Language Model Distillation
Xiaoyu Liu, Yun Zhang, Wei Li +7
Knowledge distillation plays a key role in compressing the Large Language Models (LLMs), which boosts a small-size student model under large teacher models' guidance. However, exis…
UniCompress: Enhancing Multi-Data Medical Image Compression with Knowledge Distillation
Runzhao Yang, Yinda Chen, Zhihong Zhang +6
In the field of medical image compression, Implicit Neural Representation (INR) networks have shown remarkable versatility due to their flexible compression ratios, yet they are co…
TokenUnify: Scaling Up Autoregressive Pretraining for Neuron Segmentation
Yinda Chen, Haoyuan Shi, Xiaoyu Liu +5
Neuron segmentation from electron microscopy (EM) volumes is crucial for understanding brain circuits, yet the complex neuronal structures in high-resolution EM images present sign…
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
Quan Zhang, Xiaoyu Liu, Wei Li +6
In image restoration (IR), leveraging semantic priors from segmentation models has been a common approach to improve performance. The recent segment anything model (SAM) has emerge…
BIMCV-R: A Landmark Dataset for 3D CT Text-Image Retrieval
Yinda Chen, Che Liu, Xiaoyu Liu +2
The burgeoning integration of 3D medical imaging into healthcare has led to a substantial increase in the workload of medical professionals. To assist clinicians in their diagnosti…