Xianggen Liu - RankMe

45 papers A* 8A 2Journal 31Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DCA-Net: Graph-based dependent sampling and dynamic context association for biomedical trigger detection. Inf. Sci. Zilin Wang, Jiancheng Lv, Xianggen Liu
2026	J	`jnl`	ProtoDiff: Prototypical Diffusion Model for Few-Shot Molecular Image Generation. IEEE Trans. Comput. Biol. Bioinform. Wenhao Zheng, Peidong Liu, Hanwen Zhang, Chenwei Sun, Xiong Deng, Xianggen Liu, Jiancheng Lv
2025	J	`jnl`	Client Selection in Federated Learning for Industry 5.0: A Heuristic-Guided Pointer Network Reinforcement Learning Approach. IEEE Trans. Ind. Informatics Cheng Dai, Shoupeng Lu, Peng Wang, Hao Yin, Yijing Wang, Xianggen Liu, Bing Guo
2025	J	`jnl`	GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model. Big Data Min. Anal. Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv
2025	J	`jnl`	MolEM: a unified generative framework for molecular graphs and sequential orders. Briefings Bioinform. Hanwen Zhang, Deng Xiong, Xianggen Liu, Jiancheng Lv
2025	A*	`conf`	Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generation. ACM Multimedia Wenhao Zheng, Chenwei Sun, Wenbo Zhang, Jiancheng Lv, Xianggen Liu
2025	J	`jnl`	Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generation. CoRR Wenhao Zheng, Chenwei Sun, Wenbo Zhang, Jiancheng Lv, Xianggen Liu
2025	J	`jnl`	TargetSA: adaptive simulated annealing for target-specific drug design. Bioinform. Zhe Xue, Chenwei Sun, Wenhao Zheng, Jiancheng Lv, Xianggen Liu
2024	J	`jnl`	Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation. CoRR Peidong Liu, Wenbo Zhang, Xue Zhe, Jiancheng Lv, Xianggen Liu
2024	—	`conf`	Create! Don't Repeat: A Paradigm Shift in Multi-Label Augmentation through Label Creative Generation. NAACL-HLT Letian Wang, Xianggen Liu, Jiancheng Lv
2024	J	`jnl`	DrugLLM: Open Large Language Model for Few-shot Molecule Generation. CoRR Xianggen Liu, Yan Guo, Haoran Li, Jin Liu, Shudong Huang, Bowen Ke, Jiancheng Lv
2024	J	`jnl`	MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting. CoRR Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu
2024	A*	`conf`	MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting. AAAI Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu
2024	J	`jnl`	TimeSQL: Improving multivariate time series forecasting with multi-scale patching and smooth quadratic loss. Inf. Sci. Site Mo, Haoxin Wang, Bixiong Li, Songhai Fan, Yuankai Wu, Xianggen Liu
2023	J	`jnl`	Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition. IEEE Trans. Affect. Comput. Xinke Shen, Xianggen Liu, Xin Hu, Dan Zhang, Sen Song
2023	J	`jnl`	GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model. CoRR Caiyang Yu, Xianggen Liu, Wentao Feng, Chenwei Tang, Jiancheng Lv
2023	J	`jnl`	IML-ViT: Image Manipulation Localization by Vision Transformer. CoRR Xiaochen Ma, Bo Du, Xianggen Liu, Ahmed Y. Al Hammadi, Jizhe Zhou
2023	J	`jnl`	TimeSQL: Improving Multivariate Time Series Forecasting with Multi-Scale Patching and Smooth Quadratic Loss. CoRR Site Mo, Haoxin Wang, Bixiong Li, Songhai Fan, Yuankai Wu, Xianggen Liu
2023	—	`conf`	Vector-Quantized Prompt Learning for Paraphrase Generation. EMNLP (Findings) Haotian Luo, Yixin Liu, Peidong Liu, Xianggen Liu
2023	J	`jnl`	Vector-Quantized Prompt Learning for Paraphrase Generation. CoRR Haotian Luo, Yixin Liu, Peidong Liu, Xianggen Liu
2023	J	`jnl`	Weakly Supervised Reasoning by Neuro-Symbolic Approaches. CoRR Xianggen Liu, Zhengdong Lu, Lili Mou
2023	—	`ch.`	Weakly Supervised Reasoning by Neuro-Symbolic Approaches. Compendium of Neurosymbolic Artificial Intelligence Xianggen Liu, Zhengdong Lu, Lili Mou
2022	A*	`conf`	Abstract Rule Learning for Paraphrase Generation. IJCAI Xianggen Liu, Wenqiang Lei, Jiancheng Lv, Jizhe Zhou
2022	A*	`conf`	Learning Robust Rule Representations for Abstract Reasoning via Internal Inferences. NeurIPS Wenbo Zhang, Likai Tang, Site Mo, Xianggen Liu, Sen Song
2021	J	`jnl`	Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition. CoRR Xinke Shen, Xianggen Liu, Xin Hu, Dan Zhang, Sen Song
2021	J	`jnl`	Deep geometric representations for modeling effects of mutations on protein-protein binding affinity. PLoS Comput. Biol. Xianggen Liu, Yunan Luo, Pengyong Li, Sen Song, Jian Peng
2021	A*	`conf`	Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks. IJCAI Pengyong Li, Jun Wang, Ziliang Li, Yixuan Qiao, Xianggen Liu, Fei Ma, Peng Gao, Sen Song, Guotong Xie
2021	J	`jnl`	Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks. CoRR Pengyong Li, Jun Wang, Ziliang Li, Yixuan Qiao, Xianggen Liu, Fei Ma, Peng Gao, Seng Song, Guotong Xie
2021	J	`jnl`	Riboexp: an interpretable reinforcement learning framework for ribosome density modeling. Briefings Bioinform. Hailin Hu, Xianggen Liu, An Xiao, Yangyang Li, Chengdong Zhang, Tao Jiang, Dan Zhao, Sen Song, Jianyang Zeng
2021	J	`jnl`	Simulated annealing for optimization of graphs and sequences. CoRR Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, Huasong Zhong, Jie Zhou, Lili Mou, Sen Song
2021	J	`jnl`	Simulated annealing for optimization of graphs and sequences. Neurocomputing Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, Huasong Zhong, Jie Zhou, Lili Mou, Sen Song
2021	J	`jnl`	TrimNet: learning molecular representation from triplet messages for biomedicine. Briefings Bioinform. Pengyong Li, Yuquan Li, Chang-Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song, Xiaojun Yao
2020	A*	`conf`	A Chance-Constrained Generative Framework for Sequence Optimization. ICML Xianggen Liu, Qiang Liu, Sen Song, Jian Peng
2020	J	`jnl`	Finding decision jumps in text classification. Neurocomputing Xianggen Liu, Lili Mou, Haotian Cui, Zhengdong Lu, Sen Song
2020	J	`jnl`	Pre-training of Graph Neural Network for Modeling Effects of Mutations on Protein-Protein Binding Affinity. CoRR Xianggen Liu, Yunan Luo, Sen Song, Jian Peng
2020	A*	`conf`	Unsupervised Paraphrasing by Simulated Annealing. ACL Xianggen Liu, Lili Mou, Fandong Meng, Hao Zhou, Jie Zhou, Sen Song
2019	A	`conf`	AddressNet: Shift-Based Primitives for Efficient Convolutional Neural Networks. WACV Yihui He, Xianggen Liu, Huasong Zhong, Yuchun Ma
2019	J	`jnl`	Unsupervised Paraphrasing by Simulated Annealing. CoRR Xianggen Liu, Lili Mou, Fandong Meng, Hao Zhou, Jie Zhou, Sen Song
2018	J	`jnl`	Deep-learning Based Modeling of Fault Detachment Stability for Power Grid. CoRR Haotian Cui, Xianggen Liu, Yanhao Huang
2018	J	`jnl`	JUMPER: Learning When to Make Classification Decisions in Reading. CoRR Xianggen Liu, Lili Mou, Haotian Cui, Zhengdong Lu, Sen Song
2018	A*	`conf`	Jumper: Learning When to Make Classification Decision in Reading. IJCAI Xianggen Liu, Lili Mou, Haotian Cui, Zhengdong Lu, Sen Song
2018	—	`conf`	Object-oriented Neural Programming (OONP) for Document Understanding. ACL (1) Zhengdong Lu, Xianggen Liu, Haotian Cui, Yukun Yan, Daqi Zheng
2018	J	`jnl`	Shift-based Primitives for Efficient Convolutional Neural Networks. CoRR Huasong Zhong, Xianggen Liu, Yihui He, Yuchun Ma
2017	J	`jnl`	Object-oriented Neural Programming (OONP) for Document Understanding. CoRR Zhengdong Lu, Haotian Cui, Xianggen Liu, Yukun Yan, Daqi Zheng
2014	A	`conf`	Semantical Information Graph Model toward Fast Information Valuation in Large Teamwork. ECAI Yulin Zhang, Yang Xu, Haixiao Hu, Xianggen Liu