5 citations · 11 across the 13 of their papers we have counts for
16 papers
EgoJEPA: Beyond Retargeting for Dexterous Manipulation from Egocentric Videos
Meng Cao, Can Zhao, Jinjie Wei +12
Egocentric human videos offer a scalable alternative to costly robot demonstra- tions, yet transferring their manipulation priors to robot control remains chal- lenging. The common…
UniWAM Technical Report: Unified Mobile Manipulation via Mixed-Stream World-Action Modeling and Manipulation Anchor Pose Supervision
Wei Xue, Keliang Liu, Mingzhang Cui +14
Mobile manipulation requires precise navigation to a manipulation-ready pose followed by reliable object interaction. These two stages differ in action spaces and visual requiremen…
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Open World MRI Reconstruction with Bias-Calibrated Adaptation
Jiyao Liu, Shangqi Gao, Lihao Liu +5
Real-world MRI reconstruction systems face the open-world challenge: test data from unseen imaging centers, anatomical structures, or acquisition protocols can differ drastically f…
MedQ-Deg: A Multidimensional Benchmark for Evaluating MLLMs Across Medical Image Quality Degradations
Jiyao Liu, Junzhi Ning, Chenglong Ma +14
Despite impressive performance on standard benchmarks, multimodal large language models (MLLMs) face critical challenges in real-world clinical environments where medical images in…
MedQ-Bench: Evaluating and Exploring Medical Image Quality Assessment Abilities in MLLMs
Jiyao Liu, Jinjie Wei, Wanying Qu +17
Medical Image Quality Assessment (IQA) serves as the first-mile safety gate for clinical AI, yet existing approaches remain constrained by scalar, score-based metrics and fail to r…
Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents
Jinjie Wei, Jiyao Liu, Lihao Liu +8
Graphical User Interface (GUI) agents have made significant progress in automating digital tasks through the utilization of computer vision and language models. Nevertheless, exist…
MCCD: Multi-Agent Collaboration-based Compositional Diffusion for Complex Text-to-Image Generation
Mingcheng Li, Xiaolu Hou, Ziyang Liu +7
Diffusion models have shown excellent performance in text-to-image generation. Nevertheless, existing methods often suffer from performance bottlenecks when handling complex prompt…
BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation
Xiaolu Hou, Mingcheng Li, Dingkang Yang +7
With the widespread use of virtual reality applications, 3D scene generation has become a new challenging research frontier. 3D scenes have highly complex structures and need to en…
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning
Mingcheng Li, Dingkang Yang, Yang Liu +11
Multimodal Sentiment Analysis (MSA) is an important research area that aims to understand and recognize human sentiment through multiple modalities. The complementary information p…
MedAide: Information Fusion and Anatomy of Medical Intents via LLM-based Agent Collaboration
Dingkang Yang, Jinjie Wei, Mingcheng Li +8
In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. L…
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
Dingkang Yang, Dongling Xiao, Jinjie Wei +4
Despite their remarkable capabilities, Large Language Models (LLMs) are prone to generate responses that contradict verifiable facts, i.e., unfaithful hallucination content. Existi…
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
Dingkang Yang, Jinjie Wei, Dongling Xiao +11
Developing intelligent pediatric consultation systems offers promising prospects for improving diagnostic efficiency, especially in China, where healthcare resources are scarce. De…
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models
Jiawei Chen, Dingkang Yang, Yue Jiang +4
In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdiscipli…
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?
Jiawei Chen, Yue Jiang, Dingkang Yang +4
While Large Language Models (LLMs) excel in world knowledge understanding, adapting them to specific subfields requires precise adjustments. Due to the model's vast scale, traditio…
Debiased Multimodal Understanding for Human Language Sequences
Zhi Xu, Dingkang Yang, Mingcheng Li +5
Human multimodal language understanding (MLU) is an indispensable component of expression analysis (e.g., sentiment or humor) from heterogeneous modalities, including visual postur…