Xuefei Ning
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
48
Venues
18
Active years
2017–2026
Best venue rank
A*
Where they publish
Papers
48 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | GENMAC: Compositional Text-to-Video Generation with Multi-Agent Collaboration. | Kaiyi Huang, Yukun Huang, Xuefei Ning, Zinan Lin, Yu Wang, Xihui Liu |
| 2026 | DATE | Endor: Exploit Nearly-Decode-Only Opportunities of LLM Reasoning on Near-Memory Architecture. | Jun Liu, Tianlang Zhao, Shiyi Liu, Jiancai Ye, Lin Li, Zhen Yu, Li Ding, Hao Zhou, Zhenhua Zhu, Xuefei Ning, Yuan Xie, Yu Wang, Guohao Dai |
| 2026 | EACL | How Quantization Shapes Bias in Large Language Models. | Federico Marcuzzi, Xuefei Ning, Roy Schwartz, Iryna Gurevych |
| 2025 | AAAI | Training-Free and Hardware-Friendly Acceleration for Diffusion Models via Similarity-based Token Pruning. | Evelyn Zhang, Jiayi Tang, Xuefei Ning, Linfeng Zhang |
| 2025 | CVPR | ProReflow: Progressive Reflow with Decomposed Velocity. | Lei Ke, Haohang Xu, Xuefei Ning, Yu Li, Jiajun Li, Haoling Li, Yuxuan Lin, Dongsheng Jiang, Yujiu Yang, Linfeng Zhang |
| 2025 | CVPR | MBQ: Modality-Balanced Quantization for Large Vision-Language Models. | Shiyao Li, Yingchun Hu, Xuefei Ning, Xihui Liu, Ke Hong, Xiaotao Jia, Xiuhong Li, Yaqi Yan, Pei Ran, Guohao Dai, Shengen Yan, Huazhong Yang, Yu Wang |
| 2025 | CVPR | Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning. | Qianli Ma, Xuefei Ning, Dongrui Liu, Li Niu, Linfeng Zhang |
| 2025 | DAC | PARO: Hardware-Software Co-design with Pattern-aware Reorder-based Attention Quantization in Video Generation Models. | Xinhao Yang, Tianchen Zhao, Hongyi Wang, Wenheng Ma, Shulin Zeng, Zhenhua Zhu, Xuefei Ning, Huazhong Yang, Yu Wang |
| 2025 | EMNLP | Efficient Inference for Large Language Models -Algorithm, Model, and System. | Xuefei Ning, Guohao Dai, Haoli Bai, Lu Hou, Yu Wang, Qun Liu |
| 2025 | FPGA | FMC-LLM: Enabling FPGAs for Efficient Batched Decoding of 70B+ LLMs with a Memory-Centric Streaming Architecture. | Wenheng Ma, Xinhao Yang, Shulin Zeng, Tengxuan Liu, Libo Shen, Hongyi Wang, Shiyao Li, Jiewen Wang, Yuhan Zhang, Hao Guo, Jintao Li, Ziming Zhang, Zhenhua Zhu, Xuefei Ning, Tsung-Yi Ho, Guohao Dai, Yu Wang |
| 2025 | HPCA | TB-STC: Transposable Block-wise N: M Structured Sparse Tensor Core. | Jun Liu, Shulin Zeng, Junbo Zhao, Li Ding, Zeyu Wang, Jinhao Li, Zhenhua Zhu, Xuefei Ning, Chen Zhang, Yu Wang, Guohao Dai |
| 2025 | ICCV | FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models. | Tianyu Fu, Tengxuan Liu, Qinghao Han, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang |
| 2025 | ICLR | Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. | Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang |
| 2025 | ICLR | Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching. | Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin |
| 2025 | ICLR | Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding. | Yao Teng, Han Shi, Xian Liu, Xuefei Ning, Guohao Dai, Yu Wang, Zhenguo Li, Xihui Liu |
| 2025 | ICLR | ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation. | Tianchen Zhao, Tongcheng Fang, Haofeng Huang, Rui Wan, Widyadewi Soedarmadji, Enshu Liu, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang |
| 2025 | WWW | AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms. | Yuwei Yan, Yu Shang, Qingbin Zeng, Yu Li, Keyu Zhao, Zhiheng Zheng, Xuefei Ning, Tianji Wu, Shengen Yan, Yu Wang, Fengli Xu, Yong Li |
| 2024 | CVPR | FlashEval: Towards Fast and Accurate Evaluation of Text-to-Image Diffusion Generative Models. | Lin Zhao, Tianchen Zhao, Zinan Lin, Xuefei Ning, Guohao Dai, Huazhong Yang, Yu Wang |
| 2024 | DATE | DyPIM: Dynamic-Inference-Enabled Processing - In-Memory Accelerator. | Tongxin Xie, Tianchen Zhao, Zhenhua Zhu, Xuefei Ning, Bing Li, Guohao Dai, Huazhong Yang, Yu Wang |
| 2024 | ECCV | MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization. | Tianchen Zhao, Xuefei Ning, Tongcheng Fang, Enshu Liu, Guyue Huang, Zinan Lin, Shengen Yan, Guohao Dai, Yu Wang |
| 2024 | FPGA | FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs. | Shulin Zeng, Jun Liu, Guohao Dai, Xinhao Yang, Tianyu Fu, Hongyi Wang, Wenheng Ma, Hanbo Sun, Shiyao Li, Zixiao Huang, Yadong Dai, Jintao Li, Zehao Wang, Ruoyu Zhang, Kairui Wen, Xuefei Ning, Yu Wang |
| 2024 | ICCAD | Towards Floating Point-Based Attention-Free LLM: Hybrid PIM with Non-Uniform Data Format and Reduced Multiplications. | Lidong Guo, Zhenhua Zhu, Tengxuan Liu, Xuefei Ning, Shiyao Li, Guohao Dai, Huazhong Yang, Wangyang Fu, Yu Wang |
| 2024 | ICLR | Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. | Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko |
| 2024 | ICLR | A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models. | Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang |
| 2024 | ICLR | Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation. | Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang |
| 2024 | ICML | Evaluating Quantized Large Language Models. | Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang |
| 2024 | WACV | TCP: Triplet Contrastive-relationship Preserving for Class-Incremental Learning. | Shiyao Li, Xuefei Ning, Shanghang Zhang, Lidong Guo, Tianchen Zhao, Huazhong Yang, Yu Wang |
| 2024 | WACV | THInImg: Cross-modal Steganography for Presenting Talking Heads in Images. | Lin Zhao, Hongxuan Li, Xuefei Ning, Xinru Jiang |
| 2023 | AAAI | Ensemble-in-One: Ensemble Learning within Random Gated Networks for Enhanced Adversarial Robustness. | Yi Cai, Xuefei Ning, Huazhong Yang, Yu Wang |
| 2023 | AAAI | Memory-Oriented Structural Pruning for Efficient Image Restoration. | Xiangsheng Shi, Xuefei Ning, Lidong Guo, Tianchen Zhao, Enshu Liu, Yi Cai, Yuhan Dong, Huazhong Yang, Yu Wang |
| 2023 | AAAI | Dynamic Ensemble of Low-Fidelity Experts: Mitigating NAS "Cold-Start". | Junbo Zhao, Xuefei Ning, Enshu Liu, Binxin Ru, Zixuan Zhou, Tianchen Zhao, Chen Chen, Jiajin Zhang, Qingmin Liao, Yu Wang |
| 2023 | ICCV | Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection. | Tianchen Zhao, Xuefei Ning, Ke Hong, Zhongyuan Qiu, Pu Lu, Yali Zhao, Linfeng Zhang, Lipu Zhou, Guohao Dai, Huazhong Yang, Yu Wang |
| 2023 | ICML | OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models. | Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang |
| 2023 | MICRO | DF-GAS: a Distributed FPGA-as-a-Service Architecture towards Billion-Scale Graph-based Approximate Nearest Neighbor Search. | Shulin Zeng, Zhenhua Zhu, Jun Liu, Haoyu Zhang, Guohao Dai, Zixuan Zhou, Shuangchen Li, Xuefei Ning, Yuan Xie, Huazhong Yang, Yu Wang |
| 2022 | CVPR | Searching for Energy-Efficient Hybrid Adder-Convolution Neural Networks. | Wenshuo Li, Xinghao Chen, Jinyu Bai, Xuefei Ning, Yunhe Wang |
| 2022 | CVPR | FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning. | Minxue Tang, Xuefei Ning, Yitu Wang, Jingwei Sun, Yu Wang, Hai Helen Li, Yiran Chen |
| 2022 | CVPR | CodedVTR: Codebook-based Sparse Voxel Transformer with Geometric Guidance. | Tianchen Zhao, Niansong Zhang, Xuefei Ning, He Wang, Li Yi, Yu Wang |
| 2022 | DATE | Gibbon: Efficient Co-Exploration of NN Model and Processing-In-Memory Architecture. | Hanbo Sun, Chenyu Wang, Zhenhua Zhu, Xuefei Ning, Guohao Dai, Huazhong Yang, Yu Wang |
| 2022 | ECCV | CLOSE: Curriculum Learning on the Sharing Extent Towards Better One-Shot NAS. | Zixuan Zhou, Xuefei Ning, Yi Cai, Jiashu Han, Yiping Deng, Yuhan Dong, Huazhong Yang, Yu Wang |
| 2022 | VTS | Special Session: Fault-Tolerant Deep Learning: A Hierarchical Perspective. | Cheng Liu, Zhen Gao, Siting Liu, Xuefei Ning, Huawei Li, Xiaowei Li |
| 2021 | ASPDAC | Efficient Computing Platform Design for Autonomous Driving Systems. | Shuang Liang, Changcheng Tang, Xuefei Ning, Shulin Zeng, Jincheng Yu, Yu Wang, Kaiyuan Guo, Diange Yang, Tianyi Lu, Huazhong Yang |
| 2020 | ASPDAC | FTT-NAS: Discovering Fault-Tolerant Neural Architecture. | Wenshuo Li, Xuefei Ning, Guangjun Ge, Xiaoming Chen, Yu Wang, Huazhong Yang |
| 2020 | ASPDAC | Black Box Search Space Profiling for Accelerator-Aware Neural Architecture Search. | Shulin Zeng, Hanbo Sun, Yu Xing, Xuefei Ning, Yi Shan, Xiaoming Chen, Yu Wang, Huazhong Yang |
| 2020 | ECCV | DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation. | Xuefei Ning, Tianchen Zhao, Wenshuo Li, Peng Lei, Yu Wang, Huazhong Yang |
| 2020 | ECCV | A Generic Graph-Based Neural Architecture Encoding Scheme for Predictor-Based NAS. | Xuefei Ning, Yin Zheng, Tianchen Zhao, Yu Wang, Huazhong Yang |
| 2019 | FPGA | Compressed CNN Training with FPGA-based Accelerator. | Kaiyuan Guo, Shuang Liang, Jincheng Yu, Xuefei Ning, Wenshuo Li, Yu Wang, Huazhong Yang |
| 2018 | DATE | Real-time object detection towards high power efficiency. | Jincheng Yu, Kaiyuan Guo, Yiming Hu, Xuefei Ning, Jiantao Qiu, Huizi Mao, Song Yao, Tianqi Tang, Boxun Li, Yu Wang, Huazhong Yang |
| 2017 | DAC | Fault-Tolerant Training with On-Line Fault Detection for RRAM-Based Neural Computing Systems. | Lixue Xia, Mengyun Liu, Xuefei Ning, Krishnendu Chakrabarty, Yu Wang |