Segueix
Shengjie Luo
Shengjie Luo
PhD Student, Peking University
Correu electrònic verificat a stu.pku.edu.cn - Pàgina d'inici
Títol
Citada per
Citada per
Any
Do Transformers Really Perform Bad for Graph Representation?
C Ying, T Cai, S Luo, S Zheng, G Ke, D He, Y Shen, TY Liu
NeurIPS 2021, 2021
14262021
Graphnorm: A principled approach to accelerating graph neural network training
T Cai*, S Luo*, K Xu, D He, T Liu, L Wang
ICML 2021, 2021
2062021
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
B Zhang*, S Luo*, L Wang, D He
ICLR 2023 Outstanding Paper Award, 2023
1292023
One Transformer Can Understand Both 2D & 3D Molecular Data
S Luo, T Chen, Y Xu, S Zheng, TY Liu, L Wang, D He
ICLR 2023, 2022
1022022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
Y Shi, S Zheng, G Ke, Y Shen, J You, J He, S Luo, C Liu, D He, TY Liu
arXiv preprint arXiv:2203.04810, 2022
702022
Your Transformer May Not be as Powerful as You Expect
S Luo, S Li, S Zheng, TY Liu, L Wang, D He
NeurIPS 2022, 2022
522022
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding
S Luo, S Li, T Cai, D He, D Peng, S Zheng, G Ke, L Wang, TY Liu
NeurIPS 2021, 2021
522021
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
S Luo, T Chen, AS Krishnapriyan
ICLR 2024 Spotlight Presentation, 2024
182024
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track
C Ying, M Yang, S Zheng, G Ke, S Luo, T Cai, C Wu, Y Wang, Y Shen, ...
KDD CUP 2021, 2021
122021
Learning a fourier transform for linear relative positional encodings in transformers
K Choromanski, S Li, V Likhosherstov, KA Dubey, S Luo, D He, Y Yang, ...
International Conference on Artificial Intelligence and Statistics, 2278-2286, 2024
92024
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
Z He*, G Feng*, S Luo*, K Yang, D He, J Xu, Z Zhang, H Yang, L Wang
ICML 2024, 2024
82024
Masked Molecule Modeling: A New Paradigm of Molecular Representation Learning for Chemistry Understanding
J He, K Tian, S Luo, Y Min, S Zheng, Y Shi, D He, H Liu, N Yu, L Wang, ...
72022
How Numerical Precision Affects Mathematical Reasoning Capabilities of LLMs
G Feng, K Yang, Y Gu, X Ai, S Luo, J Sun, D He, Z Li, L Wang
arXiv preprint arXiv:2410.13857, 2024
42024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
T Chen*, S Luo*, D He, S Zheng, TY Liu, L Wang
ICML 2024, 2023
42023
Bridging Geometric States via Geometric Diffusion Bridge
S Luo, Y Xu, D He, S Zheng, TY Liu, L Wang
NeurIPS 2024, 2024
12024
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning
Y Ren, D Zheng, C Liu, P Jin, Y Shi, L Huang, J He, S Luo, T Qin, TY Liu
NeurIPS 2024, 2024
12024
Revisiting Language Encoding in Learning Multilingual Representations
S Luo, K Gao, S Zheng, G Ke, D He, L Wang, TY Liu
arXiv preprint arXiv:2102.08357, 2021
12021
Let the Code LLM Edit Itself When You Edit the Code
Z He, J Zhang, S Luo, J Xu, Z Zhang, D He
ICLR 2025, 2024
2024
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
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