A Multi-dimension Measurement Study of a Large Scale Campus WiFi Network. - Congcong Miao; Jilong Wang 001; Hui Wang 011; Jun Zhang 004; Weiwei Zhou; Shengchao Liu (LCN, 2018)

ATOMO: Communication-efficient Learning via Atomic Sparsification. - Hongyi Wang 001; Scott Sievert; Shengchao Liu; Zachary Charles; Dimitris S. Papailiopoulos; Stephen J. Wright 001 (NeurIPS, 2018)

N-Gram Graph, A Novel Molecule Representation. - Shengchao Liu; Thevaa Chandereng; Yingyu Liang (CoRR, 2018)

Dissecting persistent instability of web service: A joint perspective of server schedule dynamics and path latency. - Jing'an Xue; Jilong Wang 001; Shengchao Liu; Xiulin Ma; Haibo Wang 004 (Int. J. Commun. Syst., 2018)

Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning. - Shengchao Liu; Yingyu Liang; Anthony Gitter (AAAI, 2019)

WRT: Constructing Users' Web Request Trees from HTTP Header Logs. - Shengchao Liu; Jilong Wang 001; Hui Wang 011; Haibo Wang 004; Ya Liu (ICC, 2019)

A Generalized Moving Average Filter for Active Power Filter Applications. - Yalan Gu; Shengchao Liu; Dong Wang; Li Zhang (ISIE, 2019)

Evaluation of Hybrid Si/SiC Three-Level Active Neutral-Point-Clamped Inverters. - Li Zhang; Shengchao Liu; Guang Chen; Xingjian Yang (ISIE, 2019)

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules. - Shengchao Liu; Mehmet Furkan Demirel; Yingyu Liang (NeurIPS, 2019)

Practical Model Selection for Prospective Virtual Screening. - Shengchao Liu; Moayad Alnammi; Spencer S. Ericksen; Andrew F. Voter; Gene E. Ananiev; James L. Keck; F. Michael Hoffmann; Scott A. Wildman; Anthony Gitter (J. Chem. Inf. Model., 2019)

Learning Drug Functions from Chemical Structures with Convolutional Neural Networks and Random Forests. - Jesse G. Meyer; Shengchao Liu; Ian J. Miller; Joshua J. Coon; Anthony Gitter (J. Chem. Inf. Model., 2019)

An Adaptive Online Scheme for Scheduling and Resource Enforcement in Storm. - Shengchao Liu; Jianping Weng; Jessie Hui Wang; Changqing An; Yipeng Zhou; Jilong Wang 001 (IEEE/ACM Trans. Netw., 2019)

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Simon Blackburn; Karam M. J. Thomas; Connor W. Coley; Jian Tang 005; Sarath Chandar; Yoshua Bengio (ICML, 2020)

Bad Global Minima Exist and SGD Can Reach Them. - Shengchao Liu; Dimitris S. Papailiopoulos; Dimitris Achlioptas (NeurIPS, 2020)

Achieving User-Defined Location Privacy Preservation Using a P2P System. - Shengchao Liu; Jessie Hui Wang; Jilong Wang 001; Qianli Zhang (IEEE Access, 2020)

Neural Sentence Ordering Based on Constraint Graphs. - Yutao Zhu 001; Kun Zhou 002; Jian-Yun Nie; Shengchao Liu; Zhicheng Dou (AAAI, 2021)

BERT4SO: Neural Sentence Ordering by Fine-tuning BERT. - Yutao Zhu 001; Jian-Yun Nie; Kun Zhou 002; Shengchao Liu; Pan Du 001 (CoRR, 2021)

An Analysis of Attentive Walk-Aggregating Graph Neural Networks. - Mehmet Furkan Demirel; Shengchao Liu; Siddhant Garg; Yingyu Liang (CoRR, 2021)

Structured Multi-task Learning for Molecular Property Prediction. - Shengchao Liu; Meng Qu; Zuobai Zhang; Huiyu Cai; Jian Tang 005 (AISTATS, 2022)

Pre-training Molecular Graph Representation with 3D Geometry. - Shengchao Liu; Hanchen Wang 002; Weiyang Liu; Joan Lasenby; Hongyu Guo; Jian Tang 005 (ICLR, 2022)

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery. - Zhaocheng Zhu; Chence Shi; Zuobai Zhang; Shengchao Liu; Minghao Xu; Xinyu Yuan; Yangtian Zhang; Jun-Kun Chen; Huiyu Cai; Jiarui Lu; Chang Ma; Runcheng Liu; et al. (CoRR, 2022)

MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. - Yuanqi Du; Tianfan Fu; Jimeng Sun 001; Shengchao Liu (CoRR, 2022)

Augmenting Message Passing by Retrieving Similar Graphs. - Dingmin Wang; Shengchao Liu; Hanchen Wang 002; Linfeng Song; Jian Tang 005; Song Le; Bernardo Cuenca Grau; Qi Liu 049 (CoRR, 2022)

Evaluating Self-Supervised Learning for Molecular Graph Embeddings. - Hanchen Wang 002; Jean Kaddour; Shengchao Liu; Jian Tang 005; Matt J. Kusner; Joan Lasenby; Qi Liu 049 (CoRR, 2022)

Flaky Performances when Pretraining on Relational Databases. - Shengchao Liu; David Vázquez 001; Jian Tang 005; Pierre-André Noël (CoRR, 2022)

Attentive Walk-Aggregating Graph Neural Networks. - Mehmet Furkan Demirel; Shengchao Liu; Siddhant Garg; Zhenmei Shi; Yingyu Liang (Trans. Mach. Learn. Res., 2022)

Flaky Performances When Pretraining on Relational Databases (Student Abstract). - Shengchao Liu; David Vázquez 001; Jian Tang 005; Pierre-André Noël (AAAI, 2023)

An Empirical Study of Retrieval-Enhanced Graph Neural Networks. - Dingmin Wang; Shengchao Liu; Hanchen Wang 002; Bernardo Cuenca Grau; Linfeng Song; Jian Tang 005; Le Song; Qi Liu 049 (ECAI, 2023)

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching. - Shengchao Liu; Hongyu Guo; Jian Tang 005 (ICLR, 2023)

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. - Shengchao Liu; Weitao Du; Zhi-Ming Ma; Hongyu Guo; Jian Tang 005 (ICML, 2023)

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. - Weitao Du; Jiujiu Chen; Xuecang Zhang; Zhi-Ming Ma; Shengchao Liu (NeurIPS, 2023)

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. - Shengchao Liu; Weitao Du; Yanjing Li; Zhuoxinran Li; Zhiling Zheng; Chenru Duan; Zhi-Ming Ma; Omar Yaghi; Animashree Anandkumar; Christian Borgs; Jennifer T. Chayes; Hongyu Guo; et al. (NeurIPS, 2023)

Evaluating Self-Supervised Learning for Molecular Graph Embeddings. - Hanchen Wang 002; Jean Kaddour; Shengchao Liu; Jian Tang 005; Joan Lasenby; Qi Liu 049 (NeurIPS, 2023)

GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. - Haiteng Zhao; Shengchao Liu; Chang Ma; Hannan Xu; Jie Fu 001; Zhihong Deng 001; Lingpeng Kong; Qi Liu 049 (NeurIPS, 2023)

Leveraging Domain Relations for Domain Generalization. - Huaxiu Yao; Xinyu Yang 002; Xinyi Pan; Shengchao Liu; Pang Wei Koh; Chelsea Finn (CoRR, 2023)

A Text-guided Protein Design Framework. - Shengchao Liu; Yutao Zhu 001; Jiarui Lu; Zhao Xu 005; Weili Nie; Anthony Gitter; Chaowei Xiao; Jian Tang 005; Hongyu Guo; Anima Anandkumar (CoRR, 2023)

ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain Feedback. - Shengchao Liu; Jiongxiao Wang; Yijin Yang; Chengpeng Wang; Ling Liu 001; Hongyu Guo; Chaowei Xiao (CoRR, 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

ChemSpacE: Interpretable and Interactive Chemical Space Exploration. - Yuanqi Du; Xian Liu; Nilay Mahesh Shah; Shengchao Liu; Jieyu Zhang; Bolei Zhou (Trans. Mach. Learn. Res., 2023)

Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries. - Moayad Alnammi; Shengchao Liu; Spencer S. Ericksen; Gene E. Ananiev; Andrew F. Voter; Song Guo; James L. Keck; F. Michael Hoffmann; Scott A. Wildman; Anthony Gitter (J. Chem. Inf. Model., 2023)

Multi-modal molecule structure-text model for text-based retrieval and editing. - Shengchao Liu; Weili Nie; Chengpeng Wang; Jiarui Lu; Zhuoran Qiao; Ling Liu 001; Jian Tang 005; Chaowei Xiao; Animashree Anandkumar (Nat. Mac. Intell., 2023)

Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better. - Shengchao Liu; Xiaoming Liu 011; Yichen Wang 002; Zehua Cheng; Chengzhengxu Li; Zhaohan Zhang; Yu Lan 001; Chao Shen 001 (ACL (1), 2024)

Conversational Drug Editing Using Retrieval and Domain Feedback. - Shengchao Liu; Jiongxiao Wang; Yijin Yang; Chengpeng Wang; Ling Liu 001; Hongyu Guo; Chaowei Xiao (ICLR, 2024)

Improving Domain Generalization with Domain Relations. - Huaxiu Yao; Xinyu Yang 002; Xinyi Pan; Shengchao Liu; Pang Wei Koh; Chelsea Finn (ICLR, 2024)

CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. - Jason Yang; Ariane Mora; Shengchao Liu; Bruce J. Wittmann; Animashree Anandkumar; Frances H. Arnold; Yisong Yue (NeurIPS, 2024)

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. - Gautham Dharuman; Kyle Hippe; Alexander Brace; Sam Foreman; Väinö Hatanpää; Varuni Katti Sastry; Huihuo Zheng; Logan T. Ward; Servesh Muralidharan; Archit Vasan; Bharat Kale; Carla M. Mann; et al. (SC, 2024)

A quatum inspired neural network for geometric modeling. - Weitao Du; Shengchao Liu; Xuecang Zhang (CoRR, 2024)

A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics. - Shengchao Liu; Weitao Du; Yanjing Li; Zhuoxinran Li; Vignesh C. Bhethanabotla; Nakul Rampal; Omar Yaghi; Christian Borgs; Anima Anandkumar; Hongyu Guo; Jennifer T. Chayes (CoRR, 2024)

Does DetectGPT Fully Utilize Perturbation? Bridge Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better. - Shengchao Liu; Xiaoming Liu 011; Yichen Wang 002; Zehua Cheng; Chengzhengxu Li; Zhaohan Zhang; Yu Lan 001; Chao Shen 001 (CoRR, 2024)

Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design. - Shengchao Liu; Divin Yan; Weitao Du; Weiyang Liu; Zhuoxinran Li; Hongyu Guo; Christian Borgs; Jennifer T. Chayes; Anima Anandkumar (CoRR, 2024)

Targetless External Reference Calibration of LiDAR and Camera in Autonomous Driving Environment. - Hao Wu 073; Yang Liu 375; Hongqian Huang; Jie Li 074; Qijing Lin; Shengchao Liu (IEEE Trans. Instrum. Meas., 2024)

Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. - Shengchao Liu; Chengpeng Wang; Jiarui Lu; Weili Nie; Hanchen Wang 002; Zhuoxinran Li; Bolei Zhou; Jian Tang 005 (Trans. Mach. Learn. Res., 2024)

AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly. - Hongyu Guo; Yoshua Bengio; Shengchao Liu (ICLR, 2025)

A text-guided protein design framework. - Shengchao Liu; Yanjing Li; Zhuoxinran Li; Anthony Gitter; Yutao Zhu 001; Jiarui Lu; Zhao Xu 005; Weili Nie; Arvind Ramanathan; Chaowei Xiao; Jian Tang 005; Hongyu Guo; et al. (Nat. Mac. Intell., 2025)

Flow Along the K-Amplitude for Generative Modeling. - Weitao Du; Shuning Chang; Jiasheng Tang; Yu Rong; Fan Wang 019; Shengchao Liu (CoRR, 2025)

Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization. - Shengchao Liu; Hannan Xu; Yan Ai; Huanxin Li; Yoshua Bengio; Harry Guo (CoRR, 2025)

MGT-Prism: Enhancing Domain Generalization for Machine-Generated Text Detection via Spectral Alignment. - Shengchao Liu; Xiaoming Liu; Chengzhengxu Li; Zhaohan Zhang; Guoxin Ma; Yu Lan; Shuai Xiao (CoRR, 2025)