activity
20232025
most citedReinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions

4 citations · 11 across the 14 of their papers we have counts for

collaborators

14 papers

cs.AI2025

Comprehensive Metapath-based Heterogeneous Graph Transformer for Gene-Disease Association Prediction

Wentao Cui, Shoubo Li, Chen Fang +4

Discovering gene-disease associations is crucial for understanding disease mechanisms, yet identifying these associations remains challenging due to the time and cost of biological…

q-bio.GN2024

scReader: Prompting Large Language Models to Interpret scRNA-seq Data

Cong Li, Qingqing Long, Yuanchun Zhou +1

Large language models (LLMs) have demonstrated remarkable advancements, primarily due to their capabilities in modeling the hidden relationships within text sequences. This innovat…

q-bio.GN2024

GeneSUM: Large Language Model-based Gene Summary Extraction

Zhijian Chen, Chuan Hu, Min Wu +4

Emerging topics in biomedical research are continuously expanding, providing a wealth of information about genes and their function. This rapid proliferation of knowledge presents…

cs.IR2024

GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation

Guojiao Lin, Zhen Meng, Dongjie Wang +3

Multimodal recommendation systems (MMRS) have received considerable attention from the research community due to their ability to jointly utilize information from user behavior and…

cs.AI20241 cited

Enhanced Gene Selection in Single-Cell Genomics: Pre-Filtering Synergy and Reinforced Optimization

Weiliang Zhang, Zhen Meng, Dongjie Wang +4

Recent advancements in single-cell genomics necessitate precision in gene panel selection to interpret complex biological data effectively. Those methods aim to streamline the anal…

cs.LG20241 cited

Enhancing Tabular Data Optimization with a Flexible Graph-based Reinforced Exploration Strategy

Xiaohan Huang, Dongjie Wang, Zhiyuan Ning +6

Tabular data optimization methods aim to automatically find an optimal feature transformation process that generates high-value features and improves the performance of downstream…