4 citations · 8 across the 16 of their papers we have counts for
8 papers · 1 filter
TRIDENT: A Trimodal Cascade Generative Framework for Drug and RNA-Conditioned Cellular Morphology Synthesis
Rui Peng, Ziru Liu, Lingyuan Ye +3
Accurately modeling the relationship between perturbations, transcriptional responses, and phenotypic changes is essential for building an AI Virtual Cell (AIVC). However, existing…
MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics
Yuxing Lu, Xukai Zhao, J. Ben Tamo +6
Large Language Models (LLMs) have demonstrated remarkable capabilities on general text; however, their proficiency in specialized scientific domains that require deep, interconnect…
Language-Guided Tuning: Configuration Optimization for Automated ML Research
Yuxing Lu, Yucheng Hu, Nan Sun +1
Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strategy, feature engineering, and hy…
DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients
Yuxing Lu, Gecheng Fu, Wei Wu +3
Existing medical RAG systems mainly leverage knowledge from medical knowledge bases, neglecting the crucial role of experiential knowledge derived from similar patient cases -- a k…
KINDLE: Knowledge-Guided Distillation for Prior-Free Gene Regulatory Network Inference
Rui Peng, Yuchen Lu, Qichen Sun +4
Gene regulatory network (GRN) inference serves as a cornerstone for deciphering cellular decision-making processes. Early approaches rely exclusively on gene expression data, thus…
Comprehensive Manuscript Assessment with Text Summarization Using 69707 articles
Qichen Sun, Yuxing Lu, Kun Xia +3
Rapid and efficient assessment of the future impact of research articles is a significant concern for both authors and reviewers. The most common standard for measuring the impact…
KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment
Yuxing Lu, Wei Wu, Xukai Zhao +2
Maintaining comprehensive and up-to-date knowledge graphs (KGs) is critical for modern AI systems, but manual curation struggles to scale with the rapid growth of scientific litera…
Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications
Yuxing Lu, Sin Yee Goi, Xukai Zhao +1
Biomedical knowledge graphs (BKGs) have emerged as powerful tools for organizing and leveraging the vast and complex data found across the biomedical field. Yet, current reviews of…