6 citations · 22 across the 21 of their papers we have counts for
22 papers
Scaling Video Pretraining for Surgical Foundation Models
Sicheng Lu, Zikai Xiao, Jianhui Wei +7
Surgical video understanding is essential for computer-assisted interventions, yet existing surgical foundation models remain constrained by limited data scale, procedural diversit…
MultiBind: A Benchmark for Attribute Misbinding in Multi-Subject Generation
Wenqing Tian, Hanyi Mao, Zhaocheng Liu +4
Subject-driven image generation is increasingly expected to support fine-grained control over multiple entities within a single image. In multi-reference workflows, users may provi…
Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
Songtao Jiang, Yuan Wang, Sibo Song +22
Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…
LongWeave: A Long-Form Generation Benchmark Bridging Real-World Relevance and Verifiability
Zikai Xiao, Fei Huang, Jianhong Tu +7
Generating long, informative, and factual outputs remains a major challenge for Large Language Models (LLMs). Existing benchmarks for long-form generation typically assess real-wor…
DentVLM: A Multimodal Vision-Language Model for Comprehensive Dental Diagnosis and Enhanced Clinical Practice
Zijie Meng, Jin Hao, Xiwei Dai +20
Diagnosing and managing oral diseases necessitate advanced visual interpretation across diverse imaging modalities and integrated information synthesis. While current AI models exc…
Knowing or Guessing? Robust Medical Visual Question Answering via Joint Consistency and Contrastive Learning
Songtao Jiang, Yuxi Chen, Sibo Song +5
In high-stakes medical applications, consistent answering across diverse question phrasings is essential for reliable diagnosis. However, we reveal that current Medical Vision-Lang…
GRIT: Graph-Regularized Logit Refinement for Zero-shot Cell Type Annotation
Tianxiang Hu, Chenyi Zhou, Jiaxiang Liu +6
Cell type annotation is a fundamental step in the analysis of single-cell RNA sequencing (scRNA-seq) data. In practice, human experts often rely on the structure revealed by princi…
MedEthicsQA: A Comprehensive Question Answering Benchmark for Medical Ethics Evaluation of LLMs
Jianhui Wei, Zijie Meng, Zikai Xiao +5
While Medical Large Language Models (MedLLMs) have demonstrated remarkable potential in clinical tasks, their ethical safety remains insufficiently explored. This paper introduces…
V2T-CoT: From Vision to Text Chain-of-Thought for Medical Reasoning and Diagnosis
Yuan Wang, Jiaxiang Liu, Shujian Gao +5
Recent advances in multimodal techniques have led to significant progress in Medical Visual Question Answering (Med-VQA). However, most existing models focus on global image featur…
SurgBench: A Unified Large-Scale Benchmark for Surgical Video Analysis
Jianhui Wei, Zikai Xiao, Danyu Sun +4
Surgical video understanding is pivotal for enabling automated intraoperative decision-making, skill assessment, and postoperative quality improvement. However, progress in develop…
3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks
Xiaotang Gai, Jiaxiang Liu, Yichen Li +3
Medical Visual Question Answering (Med-VQA) holds significant potential for clinical decision support, yet existing efforts primarily focus on 2D imaging with limited task diversit…
HSCR: Hierarchical Self-Contrastive Rewarding for Aligning Medical Vision Language Models
Songtao Jiang, Yan Zhang, Yeying Jin +5
Medical Vision-Language Models (Med-VLMs) have achieved success across various tasks, yet most existing methods overlook the modality misalignment issue that can lead to untrustwor…
PX2Tooth: Reconstructing the 3D Point Cloud Teeth from a Single Panoramic X-ray
Wen Ma, Huikai Wu, Zikai Xiao +3
Reconstructing the 3D anatomical structures of the oral cavity, which originally reside in the cone-beam CT (CBCT), from a single 2D Panoramic X-ray(PX) remains a critical yet chal…
Identifying and Mitigating Social Bias Knowledge in Language Models
Ruizhe Chen, Yichen Li, Jianfei Yang +3
Generating fair and accurate predictions plays a pivotal role in deploying large language models (LLMs) in the real world. However, existing debiasing methods inevitably generate u…
Joint Visual and Text Prompting for Improved Object-Centric Perception with Multimodal Large Language Models
Songtao Jiang, Yan Zhang, Chenyi Zhou +4
Multimodal Large Language Models (MLLMs) such as GPT-4V and Gemini Pro face challenges in achieving human-level perception in Visual Question Answering (VQA), particularly in objec…
MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationale
Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu +3
Medical Visual Question Answering (MedVQA), which offers language responses to image-based medical inquiries, represents a challenging task and significant advancement in healthcar…
TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement
Zhaopeng Feng, Yan Zhang, Hao Li +7
Large Language Models (LLMs) have achieved impressive results in Machine Translation (MT). However, careful evaluations by human reveal that the translations produced by LLMs still…
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu +6
Federated Long-Tailed Learning (Fed-LT), a paradigm wherein data collected from decentralized local clients manifests a globally prevalent long-tailed distribution, has garnered co…
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer
Zikai Xiao, Zihan Chen, Songshang Liu +7
Data privacy and long-tailed distribution are the norms rather than the exception in many real-world tasks. This paper investigates a federated long-tailed learning (Fed-LT) task i…
TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer
Huimin Xiong, Kunle Li, Kaiyuan Tan +6
Optical Intraoral Scanners (IOS) are widely used in digital dentistry to provide detailed 3D information of dental crowns and the gingiva. Accurate 3D tooth segmentation in IOSs is…
Fast Model Debias with Machine Unlearning
Ruizhe Chen, Jianfei Yang, Huimin Xiong +7
Recent discoveries have revealed that deep neural networks might behave in a biased manner in many real-world scenarios. For instance, deep networks trained on a large-scale face r…
Towards Distribution-Agnostic Generalized Category Discovery
Jianhong Bai, Zuozhu Liu, Hualiang Wang +7
Data imbalance and open-ended distribution are two intrinsic characteristics of the real visual world. Though encouraging progress has been made in tackling each challenge separate…