What Improves the Generalization of Graph Transformers? A Theoretical
Dive into the Self-attention and Positional Encoding

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding

4 June 2024

Sijia Liu

Pin-Yu Chen

Papers citing "What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding"

7 / 7 papers shown

Title
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers Hongkang Li Yihua Zhang Shuai Zhang M. Wang Sijia Liu Pin-Yu Chen MoMe 38 2 0 15 Apr 2025
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $ε$ -Greedy Exploration Shuai Zhang Hongkang Li Meng Wang Miao Liu Pin-Yu Chen Songtao Lu Sijia Liu K. Murugesan Subhajit Chaudhury 19 9 0 24 Oct 2023
How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding Yuchen Li Yuan-Fang Li Andrej Risteski 87 61 0 07 Mar 2023
Hierarchical Graph Transformer with Adaptive Node Sampling Zaixin Zhang Qi Liu Qingyong Hu Cheekong Lee 58 82 0 08 Oct 2022
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs Sohir Maskey Ron Levie Yunseok Lee Gitta Kutyniok GNN 65 53 0 01 Feb 2022
Heterogeneous Graph Transformer Ziniu Hu Yuxiao Dong Kuansan Wang Yizhou Sun 167 1,157 0 03 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 0 13 Feb 2020