1 citations · 3 across the 9 of their papers we have counts for
10 papers
Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization
Ruoxi Gao, Jiangweizhi Peng, Ziqi Chen +10
Drug discovery and development is time-consuming and resource-intensive, motivating computational approaches such as diffusion models for de novo drug design. Many such models foll…
AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science
An Luo, Jin Du, Xun Xian +12
Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large language models (LLMs) and artificial…
Can Agentic AI Match the Performance of Human Data Scientists?
An Luo, Jin Du, Fangqiao Tian +9
Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large language models (LLMs) have significa…
AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science
An Luo, Xun Xian, Jin Du +12
Large language models (LLMs) have advanced the automation of data science workflows. Yet it remains unclear whether they can critically leverage external domain knowledge as human…
An Outlook on the Opportunities and Challenges of Multi-Agent AI Systems
Fangqiao Tian, An Luo, Jin Du +12
A multi-agent AI system (MAS) is composed of multiple autonomous agents that interact, exchange information, and make decisions based on internal generative models. Recent advances…
Safeguarding Text-to-Image Generation via Inference-Time Prompt-Noise Optimization
Jiangweizhi Peng, Zhiwei Tang, Gaowen Liu +2
Text-to-Image (T2I) diffusion models are widely recognized for their ability to generate high-quality and diverse images based on text prompts. However, despite recent advances, th…
Unraveling the Gradient Descent Dynamics of Transformers
Bingqing Song, Boran Han, Shuai Zhang +2
While the Transformer architecture has achieved remarkable success across various domains, a thorough theoretical foundation explaining its optimization dynamics is yet to be fully…
On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains
Xun Xian, Ganghua Wang, Xuan Bi +5
Retrieval-Augmented Generation (RAG) has been empirically shown to enhance the performance of large language models (LLMs) in knowledge-intensive domains such as healthcare, financ…
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees
Xun Xian, Ganghua Wang, Xuan Bi +4
Safeguarding intellectual property and preventing potential misuse of AI-generated images are of paramount importance. This paper introduces a robust and agile plug-and-play waterm…
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective
Ganghua Wang, Xun Xian, Jayanth Srinivasa +4
The growing dependence on machine learning in real-world applications emphasizes the importance of understanding and ensuring its safety. Backdoor attacks pose a significant securi…