| 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 | 73 | 2024 |
| Dimmining: pruning-efficient and parallel graph mining on near-memory-computing G Dai, Z Zhu, T Fu, C Wei, B Wang, X Li, Y Xie, H Yang, Y Wang Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 47 | 2022 |
| 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 | 42 | 2024 |
| An efficient accelerator for point-based and voxel-based point cloud neural networks X Yang, T Fu, G Dai, S Zeng, K Zhong, K Hong, Y Wang 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 11 | 2023 |
| 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 | 9 | 2024 |
| A survey on efficient inference for large language models, 2024 Z Zhou, X Ning, K Hong, T Fu, J Xu, S Li, Y Lou, L Wang, Z Yuan, X Li, ... URL https://arxiv. org/abs/2404.14294, 2024 | 5 | 2024 |
| DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting T Fu, C Wei, Y Wang, R Ying Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 4 | 2024 |
| CLAP: Locality Aware and Parallel Triangle Counting with Content Addressable Memory T Fu, C Wei, Z Zhu, S Yang, Z Yu, G Dai, H Yang, Y Wang 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2023 | 3 | 2023 |
| 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 |
| Representation Learning for Frequent Subgraph Mining R Ying, T Fu, A Wang, J You, Y Wang, J Leskovec arXiv preprint arXiv:2402.14367, 2024 | 2 | 2024 |
| LessMine: Reducing Sample Space and Data Access for Dense Pattern Mining T Fu, Z Wan, G Dai, Y Wang, H Yang 2020 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2020 | 2 | 2020 |
| Can LLMs Learn by Teaching? A Preliminary Study X Ning, Z Wang, S Li, Z Lin, P Yao, T Fu, MB Blaschko, G Dai, H Yang, ... CoRR, 2024 | 1 | 2024 |
| FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Visual Language Models T Fu, T Liu, Q Han, G Dai, S Yan, H Yang, X Ning, Y Wang arXiv preprint arXiv:2501.01986, 2024 | | 2024 |
| Data processing apparatus controlling method and apparatus DAI Guohao, Z Zhu, Y Wang, S Xiao, T Fu, X Zhang US Patent App. 18/641,086, 2024 | | 2024 |
| SemSA: Semantic Sparse Attention is hidden in Large Language Models. T Fu, X Ning, B Chen, T Wu, G Zhang, G Dai, H Yang, Y Wang | | |
Guohao Dai（戴国浩）Associate Professor of Shanghai Jiao Tong UniversityEmail verificata su sjtu.edu.cn