Liu, Ning

34 publications

AAAI 2025 A Comprehensive Overhaul of Multimodal Assistant with Small Language Models Minjie Zhu, Yichen Zhu, Ning Liu, Xin Liu, Zhiyuan Xu, Chaomin Shen, Yaxin Peng

AAAI 2025 AUTE: Peer-Alignment and Self-Unlearning Boost Adversarial Robustness for Training Ensemble Models Lifeng Huang, Tian Su, Chengying Gao, Ning Liu, Qiong Huang

ICML 2025 An Efficient Private GPT Never Autoregressively Decodes Zhengyi Li, Yue Guan, Kang Yang, Yu Feng, Ning Liu, Yu Yu, Jingwen Leng, Minyi Guo

NeurIPS 2025 FreqPolicy: Efficient Flow-Based Visuomotor Policy via Frequency Consistency Yifei Su, Ning Liu, Dong Chen, Zhen Zhao, Kun Wu, Meng Li, Zhiyuan Xu, Zhengping Che, Jian Tang

TMLR 2025 Graph Theory-Based Deep Graph Similarity Learning: A Unified Survey of Pipeline, Techniques, and Challenges Zhouyang Liu, Ning Liu, Yixin Chen, Ziqing Wen, Jiezhong He, Dongsheng Li

ICML 2025 Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery Ning Liu, Yue Yu

NeurIPS 2025 SEEA-R1: Tree-Structured Reinforcement Fine-Tuning for Self-Evolving Embodied Agents Wanxin Tian, Shijie Zhang, Kevin Zhang, Xiaowei Chi, Chun-Kai Fan, Junyu Lu, Yulin Luo, Qiang Zhou, Yiming Zhao, Ning Liu, Siyu Lin, Zhiyuan Qin, Xiaozhu Ju, Shanghang Zhang, Jian Tang

NeurIPS 2024 AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking Shiqi Sun, Yantao Lu, Ning Liu, Bo Jiang, Jinchao Chen, Ying Zhang

ICLR 2024 An LLM Can Fool Itself: A Prompt-Based Adversarial Attack Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan Kankanhalli

NeurIPS 2024 EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching Xinwang Chen, Ning Liu, Yichen Zhu, Feifei Feng, Jian Tang

AAAI 2024 EPSD: Early Pruning with Self-Distillation for Efficient Model Compression Dong Chen, Ning Liu, Yichen Zhu, Zhengping Che, Rui Ma, Fachao Zhang, Xiaofeng Mou, Yi Chang, Jian Tang

AAAI 2024 FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering Zhenyu Li, Sunqi Fan, Yu Gu, Xiuxing Li, Zhichao Duan, Bowen Dong, Ning Liu, Jianyong Wang

ICML 2024 Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws Ning Liu, Yiming Fan, Xianyi Zeng, Milan Klöwer, Lu Zhang, Yue Yu

NeurIPS 2024 Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart Silling

IJCAI 2024 Personalized Federated Learning for Cross-City Traffic Prediction Yu Zhang, Hua Lu, Ning Liu, Yonghui Xu, Qingzhong Li, Lizhen Cui

AAAI 2024 T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Large Language Model Signals for Science Question Answering Lei Wang, Yi Hu, Jiabang He, Xing Xu, Ning Liu, Hui Liu, Heng Tao Shen

AAAI 2023 Alignment-Enriched Tuning for Patch-Level Pre-Trained Document Image Models Lei Wang, Jiabang He, Xing Xu, Ning Liu, Hui Liu

CVPR 2023 CP3: Channel Pruning Plug-in for Point-Based Networks Yaomin Huang, Ning Liu, Zhengping Che, Zhiyuan Xu, Chaomin Shen, Yaxin Peng, Guixu Zhang, Xinmei Liu, Feifei Feng, Jian Tang

NeurIPS 2023 Domain Agnostic Fourier Neural Operators Ning Liu, Siavash Jafarzadeh, Yue Yu

ICML 2023 Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning Hongzuo Xu, Yijie Wang, Juhui Wei, Songlei Jian, Yizhou Li, Ning Liu

ICCV 2023 ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction Jiabang He, Lei Wang, Yi Hu, Ning Liu, Hui Liu, Xing Xu, Heng Tao Shen

AISTATS 2023 INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola

CVPR 2023 ScaleKD: Distilling Scale-Aware Knowledge in Small Object Detector Yichen Zhu, Qiqi Zhou, Ning Liu, Zhiyuan Xu, Zhicai Ou, Xiaofeng Mou, Jian Tang

CVPRW 2023 SimDE: A Simple Domain Expansion Approach for Single-Source Domain Generalization Qinwei Xu, Ruipeng Zhang, Yiyan Wu, Ya Zhang, Ning Liu, Yanfeng Wang

NeurIPS 2022 Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation Yichen Zhu, Ning Liu, Zhiyuan Xu, Xin Liu, Weibin Meng, Louis Wang, Zhicai Ou, Jian Tang

ICML 2021 Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

NeurIPS 2021 MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin

NeurIPS 2021 Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang

NeurIPS 2021 Scalable Rule-Based Representation Learning for Interpretable Classification Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang

ICCV 2021 Shape Self-Correction for Unsupervised Point Cloud Understanding Ye Chen, Jinxian Liu, Bingbing Ni, Hang Wang, Jiancheng Yang, Ning Liu, Teng Li, Qi Tian

AAAI 2020 AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye

AAAI 2020 Transparent Classification with Multilayer Logical Perceptrons and Random Binarization Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang

ICCVW 2019 Pose-Guided Complementary Features Learning for Amur Tiger Re-Identification Ning Liu, Qijun Zhao, Nan Zhang, Xinhua Cheng, Jianing Zhu

AAAI 2011 Collaborative Users' Brand Preference Mining Across Multiple Domains from Implicit Feedbacks Jian Tang, Jun Yan, Lei Ji, Ming Zhang, Shaodan Guo, Ning Liu, Xianfang Wang, Zheng Chen