Latent Augmentation For Better Graph Self-Supervised Learning. - Jiashun Cheng; Man Li 003; Jia Li 009; Fugee Tsung (CoRR, 2022)

Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning. - Jiashun Cheng; Man Li 003; Jia Li 009; Fugee Tsung (AAAI, 2023)

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. - Ziqi Gao; Yifan Niu; Jiashun Cheng; Jianheng Tang; Lanqing Li; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009 (AAAI, 2023)

Deep Insights into Noisy Pseudo Labeling on Graph Data. - Botao Wang; Jia Li 009; Yang Liu 165; Jiashun Cheng; Yu Rong 001; Wenjia Wang; Fugee Tsung (NeurIPS, 2023)

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (CoRR, 2023)

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (ICLR, 2024)

Graph Pre-Training Models Are Strong Anomaly Detectors. - Jiashun Cheng; Zinan Zheng; Yang Liu 165; Jianheng Tang; Hongwei Wang; Yu Rong 001; Jia Li 009; Fugee Tsung (CoRR, 2024)

Parameter-Efficient Fine-Tuning via Circular Convolution. - Aochuan Chen; Jiashun Cheng; Zijing Liu; Ziqi Gao; Fugee Tsung; Yu Li 003; Jia Li 009 (ACL (Findings), 2025)

Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps. - Jiashun Cheng; Aochuan Chen; Nuo Chen 001; Ziqi Gao; Yuhan Li 001; Jia Li 009; Fugee Tsung (ACL (Findings), 2025)

CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer. - Yang Liu 165; Zinan Zheng; Jiashun Cheng; Fugee Tsung; Deli Zhao; Yu Rong 001; Jia Li 009 (ICLR, 2025)

A Pre-Training and Adaptive Fine-Tuning Framework for Graph Anomaly Detection. - Yunhui Liu 002; Jiashun Cheng; Jia Li 009; Fugee Tsung; Hongzhi Yin; Tieke He (CoRR, 2025)