6 citations · 18 across the 15 of their papers we have counts for
15 papers
DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning
Zijie Meng, Xiwei Dai, Yixuan Tang +6
Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from domain knowl…
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…
IOSVLM: A 3D Vision-Language Model for Unified Dental Diagnosis from Intraoral Scans
Huimin Xiong, Zijie Meng, Tianxiang Hu +3
3D intraoral scans (IOS) are increasingly adopted in routine dentistry due to abundant geometric evidence, and unified multi-disease diagnosis is desirable for clinical documentati…
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…
Persona-judge: Personalized Alignment of Large Language Models via Token-level Self-judgment
Xiaotian Zhang, Ruizhe Chen, Yang Feng +1
Aligning language models with human preferences presents significant challenges, particularly in achieving personalization without incurring excessive computational costs. Existing…
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…
Learnable Privacy Neurons Localization in Language Models
Ruizhe Chen, Tianxiang Hu, Yang Feng +1
Concerns regarding Large Language Models (LLMs) to memorize and disclose private information, particularly Personally Identifiable Information (PII), become prominent within the co…
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…
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…