Luo, Shengjie

15 publications

ICLR 2025 Let the Code LLM Edit Itself When You Edit the Code Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He

NeurIPS 2025 UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection Jigang Fan, QuanLin Wu, Shengjie Luo, Liwei Wang

NeurIPS 2024 Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICLR 2024 Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo, Tianlang Chen, Aditi S. Krishnapriyan

ICML 2024 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

AISTATS 2024 Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller

NeurIPS 2024 Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu

ICML 2024 Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang, Jingjing Xu, Zhi Zhang, Hongxia Yang, Di He

NeurIPSW 2023 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICLR 2023 One Transformer Can Understand Both 2D & 3D Molecular Data Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

ICLR 2023 Rethinking the Expressive Power of GNNs via Graph Biconnectivity Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

NeurIPS 2022 Your Transformer May Not Be as Powerful as You Expect Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

NeurIPS 2021 Do Transformers Really Perform Badly for Graph Representation? Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

ICML 2021 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang

NeurIPS 2021 Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu