5 citations · 10 across the 10 of their papers we have counts for
10 papers
PyVision: Agentic Vision with Dynamic Tooling
Shitian Zhao, Haoquan Zhang, Shaoheng Lin +4
LLMs are increasingly deployed as agents, systems capable of planning, reasoning, and dynamically calling external tools. However, in visual reasoning, prior approaches largely rem…
LeX-Art: Rethinking Text Generation via Scalable High-Quality Data Synthesis
Shitian Zhao, Qilong Wu, Xinyue Li +10
We introduce LeX-Art, a comprehensive suite for high-quality text-image synthesis that systematically bridges the gap between prompt expressiveness and text rendering fidelity. Our…
Learning to Animate Images from A Few Videos to Portray Delicate Human Actions
Haoxin Li, Yingchen Yu, Qilong Wu +3
Despite recent progress, video generative models still struggle to animate static images into videos that portray delicate human actions, particularly when handling uncommon or nov…
Expectation-Maximization as the Engine of Scalable Medical Intelligence
Wenxuan Li, Pedro R. A. S. Bassi, Tianyu Lin +19
Large, high-quality, annotated datasets are the foundation of medical AI research, but constructing even a small, moderate-quality, annotated dataset can take years of effort from…
Text-Driven Tumor Synthesis
Xinran Li, Yi Shuai, Chen Liu +11
Tumor synthesis can generate examples that AI often misses or over-detects, improving AI performance by training on these challenging cases. However, existing synthesis methods, wh…
SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
Qilong Wu, Xiaoneng Xiang, Hejia Huang +5
The rapid growth of the financial sector and the rising focus on Environmental, Social, and Governance (ESG) considerations highlight the need for advanced NLP tools. However, open…
MuMu-LLaMA: Multi-modal Music Understanding and Generation via Large Language Models
Shansong Liu, Atin Sakkeer Hussain, Qilong Wu +2
Research on large language models has advanced significantly across text, speech, images, and videos. However, multi-modal music understanding and generation remain underexplored d…
Label Critic: Design Data Before Models
Pedro R. A. S. Bassi, Qilong Wu, Wenxuan Li +4
As medical datasets rapidly expand, creating detailed annotations of different body structures becomes increasingly expensive and time-consuming. We consider that requesting radiol…
MUGen: Multi-modal Music Understanding and Generation with the Power of Large Language Models
Shansong Liu, Atin Sakkeer Hussain, Qilong Wu +2
The current landscape of research leveraging large language models (LLMs) is experiencing a surge. Many works harness the powerful reasoning capabilities of these models to compreh…
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective
Yuzheng Hu, Ruicheng Xian, Qilong Wu +3
Linear scalarization, i.e., combining all loss functions by a weighted sum, has been the default choice in the literature of multi-task learning (MTL) since its inception. In recen…