14 citations · 29 across the 19 of their papers we have counts for
22 papers
SurgLAT: Surgical Latent Attention Tracking for Depth-Aware Robotic Laparoscope Control
Rulin Zhou, Qiujie Song, Yujie Ma +10
Autonomous laparoscopic camera control requires continuous understanding of the surgeon's operative intent in dynamic surgical scenes, where the target operative region is not a st…
Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?
Jiankun Wang, Yisen Gao, Ziwei Zhang +3
Visual retrieval-augmented generation (RAG) commonly expands the retrieved evidence set to improve answer-page coverage, implicitly assuming that all available evidence should be p…
EmbodiedVAE: Disentangled Video VAE for Efficient and Controllable Embodied Manipulation
Jiayi Luo, Hanxin Zhu, Chen Gao +5
Latent diffusion models (LDMs) have recently significantly advanced embodied learning in constructing powerful embodied manipulation world models. However, despite the remarkable p…
Dysco: Dynamic Subspace Boosting to Mitigate LoRA Interference in Federated Learning
Haobo Zhang, Jiankun Wang, Suraj Rajendran +5
Federated fine-tuning of large pre-trained models increasingly relies on Low-Rank Adaptation (LoRA) to reduce communication and computation, but heterogeneous clients can make adap…
Structural Rationale Distillation via Reasoning Space Compression
Jialin Yang, Jiankun Wang, Jiajun Wu +3
When distilling reasoning from large language models (LLMs) into smaller ones, teacher rationales for similar problems often vary wildly in structure and strategy. Like a chef who…
Attention Sparsity is Input-Stable: Training-Free Sparse Attention for Video Generation via Offline Sparsity Profiling and Online QK Co-Clustering
Jiayi Luo, Jiayu Chen, Jiankun Wang +6
Diffusion Transformers (DiTs) achieve strong video generation quality but suffer from high inference cost due to dense 3D attention, motivating sparse attention techniques for impr…
SurgAtt-Tracker: Online Surgical Attention Tracking via Temporal Proposal Reranking and Motion-Aware Refinement
Rulin Zhou, Guankun Wang, An Wang +12
Accurate and stable field-of-view (FoV) guidance is critical for safe and efficient minimally invasive surgery, yet existing approaches often conflate visual attention estimation w…
EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Control
An Wang, Rulin Zhou, Mengya Xu +7
Visualizing subtle vascular motions in endoscopic surgery is crucial for surgical precision and decision-making, yet remains challenging due to the complex and dynamic nature of su…
VIGIL: Vision-Language Guided Multiple Instance Learning Framework for Ulcerative Colitis Histological Healing Prediction
Zhengxuan Qiu, Bo Peng, Xiaoying Tang +2
Objective: Ulcerative colitis (UC), characterized by chronic inflammation with alternating remission-relapse cycles, requires precise histological healing (HH) evaluation to improv…
Uni-AIMS: AI-Powered Microscopy Image Analysis
Yanhui Hong, Nan Wang, Zhiyi Xia +11
This paper presents a systematic solution for the intelligent recognition and automatic analysis of microscopy images. We developed a data engine that generates high-quality annota…
Dual Attention Driven Lumbar Magnetic Resonance Image Feature Enhancement and Automatic Diagnosis of Herniation
Lingrui Zhang, Liang Guo, Xiao An +4
Lumbar disc herniation (LDH) is a common musculoskeletal disease that requires magnetic resonance imaging (MRI) for effective clinical management. However, the interpretation of MR…
Endo-TTAP: Robust Endoscopic Tissue Tracking via Multi-Facet Guided Attention and Hybrid Flow-point Supervision
Rulin Zhou, Wenlong He, An Wang +4
Accurate tissue point tracking in endoscopic videos is critical for robotic-assisted surgical navigation and scene understanding, but remains challenging due to complex deformation…
Intelligent System for Automated Molecular Patent Infringement Assessment
Yaorui Shi, Sihang Li, Taiyan Zhang +12
Automated drug discovery offers significant potential for accelerating the development of novel therapeutics by substituting labor-intensive human workflows with machine-driven pro…
MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild
Xi Fang, Jiankun Wang, Xiaochen Cai +7
In recent decades, chemistry publications and patents have increased rapidly. A significant portion of key information is embedded in molecular structure figures, complicating larg…
A Landmark-aware Network for Automated Cobb Angle Estimation Using X-ray Images
Jie Yang, Jiankun Wang, Max Q. -H. Meng
Automated Cobb angle estimation based on X-ray images plays an important role in scoliosis diagnosis, treatment, and progression surveillance. The inadequate feature extraction and…
Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models
Jiankun Wang, Sumyeong Ahn, Taykhoom Dalal +7
Alzheimer's disease (AD) is the fifth-leading cause of death among Americans aged 65 and older. Screening and early detection of AD and related dementias (ADRD) are critical for ti…
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Hengxing Cai, Xiaochen Cai, Shuwen Yang +14
In scientific research and its application, scientific literature analysis is crucial as it allows researchers to build on the work of others. However, the fast growth of scientifi…
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang +20
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of…
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Jiankun Wang, Qianru Sun +3
Representation learning is all about discovering the hidden modular attributes that generate the data faithfully. We explore the potential of Denoising Diffusion Probabilistic Mode…
Large Language Models in Medical Term Classification and Unexpected Misalignment Between Response and Reasoning
Xiaodan Zhang, Sandeep Vemulapalli, Nabasmita Talukdar +11
This study assesses the ability of state-of-the-art large language models (LLMs) including GPT-3.5, GPT-4, Falcon, and LLaMA 2 to identify patients with mild cognitive impairment (…
MMA-Net: Multiple Morphology-Aware Network for Automated Cobb Angle Measurement
Zhengxuan Qiu, Jie Yang, Jiankun Wang
Scoliosis diagnosis and assessment depend largely on the measurement of the Cobb angle in spine X-ray images. With the emergence of deep learning techniques that employ landmark de…
Neural Network-Based Histologic Remission Prediction In Ulcerative Colitis
Yemin li, Zhongcheng Liu, Xiaoying Lou +9
BACKGROUND & AIMS: Histological remission (HR) is advocated and considered as a new therapeutic target in ulcerative colitis (UC). Diagnosis of histologic remission currently relie…