3 citations · 6 across the 13 of their papers we have counts for
13 papers
Task-Level Natural Language Priors as Learning Signals for Low-Resource LLM Training
Jian Gao, Xiao Zhang, Xun Zhu +2
Large language models (LLMs) often struggle when low-resource training data are ambiguous or incomplete. Task-level natural-language priors can provide useful guidance in such sett…
ReportQA: QA-Based Radiology Report Evaluation
Yiming Shi, Shaoshuai Yang, Xi Chen +10
Radiology report evaluation is essential for advancing automated report generation. Natural language generation metrics have limited clinical relevance. Clinical efficacy (CE) metr…
The 1st PortraitCraft Challenge: A CVPR 2026 Workshop Competition on Portrait Composition Understanding and Generation
Zijie Lou, Youyun Tang, Xiaochao Qu +40
This paper presents an overview of the inaugural PortraitCraft Challenge, held as one of the official competitions at CVPR 2026. The challenge focuses on portrait composition under…
Lost in the Hype: Revealing and Dissecting the Performance Degradation of Medical Multimodal Large Language Models in Image Classification
Xun Zhu, Fanbin Mo, Xi Chen +6
The rise of multimodal large language models (MLLMs) has sparked an unprecedented wave of applications in the field of medical imaging analysis. However, as one of the earliest and…
MIPS: a Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction
Jiaxi Wang, Yaosen Min, Xun Zhu +2
Polymers, composed of repeating structural units called monomers, are fundamental materials in daily life and industry. Accurate property prediction for polymers is essential for t…
Enhancing Multi-task Learning Capability of Medical Generalist Foundation Model via Image-centric Multi-annotation Data
Xun Zhu, Fanbin Mo, Zheng Zhang +6
The emergence of medical generalist foundation models has revolutionized conventional task-specific model development paradigms, aiming to better handle multiple tasks through join…
MedM-VL: What Makes a Good Medical LVLM?
Yiming Shi, Shaoshuai Yang, Xun Zhu +4
Medical image analysis is essential in modern healthcare. Deep learning has redirected research focus toward complex medical multimodal tasks, including report generation and visua…
Connector-S: A Survey of Connectors in Multi-modal Large Language Models
Xun Zhu, Zheng Zhang, Xi Chen +3
With the rapid advancements in multi-modal large language models (MLLMs), connectors play a pivotal role in bridging diverse modalities and enhancing model performance. However, th…
Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model
Yiming Shi, Xun Zhu, Kaiwen Wang +4
3D medical image analysis is essential for modern healthcare, yet traditional task-specific models are inadequate due to limited generalizability across diverse clinical scenarios.…
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoE
Xun Zhu, Ying Hu, Fanbin Mo +2
Multi-modal large language models (MLLMs) have shown impressive capabilities as a general-purpose interface for various visual and linguistic tasks. However, building a unified MLL…
Enhancing elusive clues in knowledge learning by contrasting attention of language models
Jian Gao, Xiao Zhang, Ji Wu +1
Causal language models acquire vast amount of knowledge from general text corpus during pretraining, but the efficiency of knowledge learning is known to be unsatisfactory, especia…
Co-occurrence is not Factual Association in Language Models
Xiao Zhang, Miao Li, Ji Wu
Pretrained language models can encode a large amount of knowledge and utilize it for various reasoning tasks, yet they can still struggle to learn novel factual knowledge effective…
TinyLLaVA Factory: A Modularized Codebase for Small-scale Large Multimodal Models
Junlong Jia, Ying Hu, Xi Weng +8
We present TinyLLaVA Factory, an open-source modular codebase for small-scale large multimodal models (LMMs) with a focus on simplicity of code implementations, extensibility of ne…