activity
20202026
most citedRPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-Training

14 citations · 32 across the 23 of their papers we have counts for

collaborators

23 papers

cs.IR2026

Beyond Paper-to-Paper: Structured Profiling and Rubric Scoring for Paper-Reviewer Matching

Yicheng Pan, Zhiyuan Ning, Ludi Wang +1

As conference submission volumes continue to grow, accurately recommending suitable reviewers has become a challenge. Most existing methods follow a ``Paper-to-Paper'' matching par…

cs.LG2025

Soft Graph Clustering for single-cell RNA Sequencing Data

Ping Xu, Pengfei Wang, Zhiyuan Ning +3

Clustering analysis is fundamental in single-cell RNA sequencing (scRNA-seq) data analysis for elucidating cellular heterogeneity and diversity. Recent graph-based scRNA-seq cluste…

cs.AI2025

Disentangled Multi-span Evolutionary Network against Temporal Knowledge Graph Reasoning

Hao Dong, Ziyue Qiao, Zhiyuan Ning +4

Temporal Knowledge Graphs (TKGs), as an extension of static Knowledge Graphs (KGs), incorporate the temporal feature to express the transience of knowledge by describing when facts…

cs.CL2025

Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linking

Yihao Ai, Zhiyuan Ning, Weiwei Dai +5

Biomedical entity linking aims to map nonstandard entities to standard entities in a knowledge base. Traditional supervised methods perform well but require extensive annotated dat…

cs.LG2025

Rethinking Graph Contrastive Learning through Relative Similarity Preservation

Zhiyuan Ning, Pengfei Wang, Ziyue Qiao +2

Graph contrastive learning (GCL) has achieved remarkable success by following the computer vision paradigm of preserving absolute similarity between augmented views. However, this…

q-bio.GN2025

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data

Ping Xu, Zhiyuan Ning, Pengjiang Li +5

Single-cell RNA sequencing (scRNA-seq) reveals cell heterogeneity, with cell clustering playing a key role in identifying cell types and marker genes. Recent advances, especially g…