6 papers
A Self-Evolving Agentic System for Automated Generation and Execution of Biological Protocols
Yankai Jiang, Weiting Tang, Haoran Sun +11
Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experimental feedback must remain…
MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization
Lisheng Zhang, Lilong Wang, Xiangyu Sun +14
Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specialized tools in multi-step workf…
Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism
Haoran Sun, Yankai Jiang, Zhenyu Tang +8
The foundation of reproducible science lies in protocols that are precise, logically ordered, and executable. The autonomous generation of these protocols through natural language…
SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents
Yankai Jiang, Wenjie Lou, Lilong Wang +17
We introduce SCP: the Science Context Protocol, an open-source standard designed to accelerate discovery by enabling a global network of autonomous scientific agents. SCP is built…
InvCoSS: Inversion-driven Continual Self-supervised Learning in Medical Multi-modal Image Pre-training
Zihao Luo, Shaohao Rui, Zhenyu Tang +2
Continual self-supervised learning (CSSL) in medical imaging trains a foundation model sequentially, alleviating the need for collecting multi-modal images for joint training and o…
Multi-modal Vision Pre-training for Medical Image Analysis
Shaohao Rui, Lingzhi Chen, Zhenyu Tang +4
Self-supervised learning has greatly facilitated medical image analysis by suppressing the training data requirement for real-world applications. Current paradigms predominantly re…