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Shengjie Luo
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2020 – today
- 2024
- [c10]Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS 2024: 2278-2286 - [c9]Shengjie Luo, Tianlang Chen, Aditi S. Krishnapriyan:
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products. ICLR 2024 - [c8]Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang, Jingjing Xu, Zhi Zhang, Hongxia Yang, Di He:
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. ICML 2024 - [c7]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. ICML 2024 - [i17]Shengjie Luo, Tianlang Chen, Aditi S. Krishnapriyan:
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products. CoRR abs/2401.10216 (2024) - [i16]Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Di He, Jingjing Xu, Zhi Zhang, Hongxia Yang, Liwei Wang:
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. CoRR abs/2401.16421 (2024) - [i15]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR abs/2406.16853 (2024) - [i14]Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He:
Let the Code LLM Edit Itself When You Edit the Code. CoRR abs/2407.03157 (2024) - [i13]Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu:
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning. CoRR abs/2410.10118 (2024) - [i12]Guhao Feng, Kai Yang, Yuntian Gu, Xinyue Ai, Shengjie Luo, Jiacheng Sun, Di He, Zhenguo Li, Liwei Wang:
How Numerical Precision Affects Mathematical Reasoning Capabilities of LLMs. CoRR abs/2410.13857 (2024) - [i11]Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
Bridging Geometric States via Geometric Diffusion Bridge. CoRR abs/2410.24220 (2024) - 2023
- [j2]Zhigang Liu, Shengjie Luo, Yiting Wang
:
Mix MSTAR: A Synthetic Benchmark Dataset for Multi-Class Rotation Vehicle Detection in Large-Scale SAR Images. Remote. Sens. 15(18): 4558 (2023) - [c6]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR 2023 - [c5]Bohang Zhang, Shengjie Luo, Liwei Wang, Di He:
Rethinking the Expressive Power of GNNs via Graph Biconnectivity. ICLR 2023 - [i10]Bohang Zhang, Shengjie Luo, Liwei Wang, Di He:
Rethinking the Expressive Power of GNNs via Graph Biconnectivity. CoRR abs/2301.09505 (2023) - [i9]Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR abs/2302.01925 (2023) - 2022
- [j1]Ke Wang
Salient-VPR: Salient Weighted Global Descriptor for Visual Place Recognition. IEEE Trans. Instrum. Meas. 71: 1-8 (2022) - [c4]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. NeurIPS 2022 - [i8]Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu:
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR abs/2203.04810 (2022) - [i7]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. CoRR abs/2205.13401 (2022) - [i6]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Di He, Liwei Wang:
One Transformer Can Understand Both 2D & 3D Molecular Data. CoRR abs/2210.01765 (2022) - 2021
- [c3]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. ICML 2021: 1204-1215 - [c2]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS 2021: 22795-22807 - [c1]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Badly for Graph Representation? NeurIPS 2021: 28877-28888 - [i5]Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu:
Revisiting Language Encoding in Learning Multilingual Representations. CoRR abs/2102.08357 (2021) - [i4]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Bad for Graph Representation? CoRR abs/2106.05234 (2021) - [i3]Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He:
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track. CoRR abs/2106.08279 (2021) - [i2]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR abs/2106.12566 (2021) - 2020
- [i1]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR abs/2009.03294 (2020)
Coauthor Index
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