12 papers
Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning
Chen Tang, Yizhou Wang, Jianyu Wu +26
Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge from spatial, chemical and pe…
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…
GGBound: A Genome-Grounded Agent for Microbial Life-Boundary Prediction
Hanbo Huang, Xuan Gong, Jing Wang +4
Characterizing the physiological life boundaries of microbial strains, including viable temperature, pH, salinity, substrate utilization, and morphology, is central to biotechnolog…
ViraHinter: a dual-modal artificial intelligence framework for predicting virus-host interactions
Weiqiang Bai, Fei Wang, Jialin Wang +10
Protein-protein interactions (PPIs) between a virus and its host govern infection, replication, and pathogenesis. While high-throughput mapping has identified thousands of virus-ho…
SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
Shuizhou Chen, Lang Yu, Xueqin Lin +12
Virtual-cell models aim to predict how cell populations respond to perturbations, but control and treated cells are measured as unpaired populations, complicating the learning of p…
Discovery of Interpretable Physical Laws in Materials via Language-Model-Guided Symbolic Regression
Yifeng Guan, Chuyi Liu, Dongzhan Zhou +4
Discovering interpretable physical laws from high-dimensional data is a fundamental challenge in scientific research. Traditional methods, such as symbolic regression, often produc…
One Brain, Omni Modalities: Towards Unified Non-Invasive Brain Decoding with Large Language Models
Changli Tang, Shurui Li, Junliang Wang +8
Deciphering brain function through non-invasive recordings requires synthesizing complementary high-frequency electromagnetic (EEG/MEG) and low-frequency metabolic (fMRI) signals.…
Sci-CoE: Co-evolving Scientific Reasoning LLMs via Geometric Consensus with Sparse Supervision
Xiaohan He, Shiyang Feng, Songtao Huang +4
Large language models (LLMs) have demonstrated exceptional reasoning capabilities, and co-evolving paradigms have shown promising results in domains with verifiable reward signals,…
SciEvalKit: An Open-source Evaluation Toolkit for Scientific General Intelligence
Yiheng Wang, Yixin Chen, Shuo Li +33
We introduce SciEvalKit, a unified benchmarking toolkit designed to evaluate AI models for science across a broad range of scientific disciplines and task capabilities. Unlike gene…
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…
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…