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Deep Prompt Tuning for Graph Transformers

Deep Prompt Tuning for Graph Transformers

18 September 2023
Reza Shirkavand
Heng-Chiao Huang
ArXivPDFHTML

Papers citing "Deep Prompt Tuning for Graph Transformers"

6 / 6 papers shown
Title
How Powerful are Spectral Graph Neural Networks
How Powerful are Spectral Graph Neural Networks
Xiyuan Wang
Muhan Zhang
70
175
0
23 May 2022
Graph Neural Networks with Learnable Structural and Positional
  Representations
Graph Neural Networks with Learnable Structural and Positional Representations
Vijay Prakash Dwivedi
A. Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
GNN
182
304
0
15 Oct 2021
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally
  Across Scales and Tasks
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Xiao Liu
Kaixuan Ji
Yicheng Fu
Weng Lam Tam
Zhengxiao Du
Zhilin Yang
Jie Tang
VLM
236
780
0
14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
278
3,784
0
18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
241
1,898
0
31 Dec 2020
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
157
1,748
0
02 Mar 2017
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