| A survey on efficient inference for large language models Z Zhou, X Ning, K Hong, T Fu, J Xu, S Li, Y Lou, L Wang, Z Yuan, X Li, ... arXiv preprint arXiv:2404.14294, 2024 | 77 | 2024 |
| Evaluating quantized large language models S Li, X Ning, L Wang, T Liu, X Shi, S Yan, G Dai, H Yang, Y Wang Forty-first International Conference on Machine Learning, 2024 | 49 | 2024 |
| Flightllm: Efficient large language model inference with a complete mapping flow on fpgas S Zeng, J Liu, G Dai, X Yang, T Fu, H Wang, W Ma, H Sun, S Li, Z Huang, ... Proceedings of the 2024 ACM/SIGDA International Symposium on Field …, 2024 | 44 | 2024 |
| Lv-eval: A balanced long-context benchmark with 5 length levels up to 256k T Yuan, X Ning, D Zhou, Z Yang, S Li, M Zhuang, Z Tan, Z Yao, D Lin, B Li, ... arXiv preprint arXiv:2402.05136, 2024 | 18 | 2024 |
| LLM-MQ: Mixed-precision Quantization for Efficient LLM Deployment S Li, X Ning, K Hong, T Liu, L Wang, X Li, K Zhong, G Dai, H Yang, ... NeurIPS 2023 Efficient Natural Language and Speech Processing Workshop, 2023, 0 | 16* | |
| Moa: Mixture of sparse attention for automatic large language model compression T Fu, H Huang, X Ning, G Zhang, B Chen, T Wu, H Wang, Z Huang, S Li, ... arXiv preprint arXiv:2406.14909, 2024 | 12 | 2024 |
| Vidit-q: Efficient and accurate quantization of diffusion transformers for image and video generation T Zhao, T Fang, E Liu, R Wan, W Soedarmadji, S Li, Z Lin, G Dai, S Yan, ... arXiv preprint arXiv:2406.02540, 2024 | 9 | 2024 |
| A unified FPGA virtualization framework for general-purpose deep neural networks in the cloud S Zeng, G Dai, H Sun, J Liu, S Li, G Ge, K Zhong, K Guo, Y Wang, H Yang ACM Transactions on Reconfigurable Technology and Systems (TRETS) 15 (3), 1-31, 2021 | 5 | 2021 |
| Towards high-accuracy and real-time two-stage small object detection on FPGA S Li, Z Zhu, H Sun, X Ning, G Dai, Y Hu, H Yang, Y Wang IEEE Transactions on Circuits and Systems for Video Technology, 2024 | 4 | 2024 |
| Can LLMs learn by teaching for better reasoning? A preliminary study X Ning, Z Wang, S Li, Z Lin, P Yao, T Fu, MB Blaschko, G Dai, H Yang, ... arXiv preprint arXiv:2406.14629, 2024 | 2 | 2024 |
| Tcp: Triplet contrastive-relationship preserving for class-incremental learning S Li, X Ning, S Zhang, L Guo, T Zhao, H Yang, Y Wang Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 2 | 2024 |
| Enabling fast 2-bit llm on gpus: Memory alignment, sparse outlier, and asynchronous dequantization J Li, S Li, J Xu, S Huang, Y Lian, J Liu, Y Wang, G Dai arXiv preprint arXiv:2311.16442, 2023 | 2 | 2023 |
| Memory-efficient and real-time SPAD-based dToF depth sensor with spatial and statistical correlation S Li, Z Zhu, Y Zhu, Q Zhu, J Zhang, W Sun, G Dai, F Qiao, H Yang, ... 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 1 | 2023 |
| MBQ: Modality-Balanced Quantization for Large Vision-Language Models S Li, Y Hu, X Ning, X Liu, K Hong, X Jia, X Li, Y Yan, P Ran, G Dai, S Yan, ... arXiv preprint arXiv:2412.19509, 2024 | | 2024 |
| CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios L Wang, S Li, X Ning, Z Yuan, S Yan, G Dai, Y Wang arXiv preprint arXiv:2409.10593, 2024 | | 2024 |
| Towards Floating Point-Based Attention-Free LLM: Hybrid PIM with Non-Uniform Data Format and Reduced Multiplications L Guo, Z Zhu, T Liu, X Ning, S Li, G Dai, H Yang, W Fu, Y Wang | | 2024 |
Yu Wang (汪玉)Department of Electronic Engineering, Tsinghua University, ChinaПідтверджена електронна адреса в mail.tsinghua.edu.cn
