| Graph neural networks: A review of methods and applications J Zhou, G Cui, S Hu, Z Zhang, C Yang, Z Liu, L Wang, C Li, M Sun AI open 1, 57-81, 2020 | 7172 | 2020 |
| Parameter-efficient fine-tuning of large-scale pre-trained language models N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ... Nature Machine Intelligence 5 (3), 220-235, 2023 | 738 | 2023 |
| Knowledgeable prompt-tuning: Incorporating knowledge into prompt verbalizer for text classification S Hu, N Ding, H Wang, Z Liu, J Li, M Sun | 398 | 2021 |
| Enhancing chat language models by scaling high-quality instructional conversations N Ding, Y Chen, B Xu, Y Qin, Z Zheng, S Hu, Z Liu, M Sun, B Zhou arXiv preprint arXiv:2305.14233, 2023 | 389 | 2023 |
| Tool learning with foundation models Y Qin, S Hu, Y Lin, W Chen, N Ding, G Cui, Z Zeng, X Zhou, Y Huang, ... ACM Computing Surveys 57 (4), 1-40, 2024 | 326 | 2024 |
| Openprompt: An open-source framework for prompt-learning N Ding, S Hu, W Zhao, Y Chen, Z Liu, HT Zheng, M Sun arXiv preprint arXiv:2111.01998, 2021 | 324 | 2021 |
| Minicpm-v: A gpt-4v level mllm on your phone Y Yao, T Yu, A Zhang, C Wang, J Cui, H Zhu, T Cai, H Li, W Zhao, Z He, ... arXiv preprint arXiv:2408.01800, 2024 | 257 | 2024 |
| Delta tuning: A comprehensive study of parameter efficient methods for pre-trained language models N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ... arXiv preprint arXiv:2203.06904, 2022 | 242 | 2022 |
| Minicpm: Unveiling the potential of small language models with scalable training strategies S Hu, Y Tu, X Han, C He, G Cui, X Long, Z Zheng, Y Fang, Y Huang, ... arXiv preprint arXiv:2404.06395, 2024 | 235 | 2024 |
| Prototypical verbalizer for prompt-based few-shot tuning G Cui, S Hu, N Ding, L Huang, Z Liu arXiv preprint arXiv:2203.09770, 2022 | 108 | 2022 |
| Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems C He, R Luo, Y Bai, S Hu, ZL Thai, J Shen, J Hu, X Han, Y Huang, ... arXiv preprint arXiv:2402.14008, 2024 | 90 | 2024 |
| Graph Policy Network for Transferable Active Learning on Graphs S Hu, Z Xiong, M Qu, X Yuan, MA Côté, Z Liu, J Tang NeurIPS'20, 2020 | 80 | 2020 |
| Bench: Extending Long Context Evaluation Beyond 100K Tokens X Zhang, Y Chen, S Hu, Z Xu, J Chen, MK Hao, X Han, ZL Thai, S Wang, ... arXiv preprint arXiv:2402.13718, 2024 | 69 | 2024 |
| Decoder-only or encoder-decoder? interpreting language model as a regularized encoder-decoder Z Fu, W Lam, Q Yu, AMC So, S Hu, Z Liu, N Collier arXiv preprint arXiv:2304.04052, 2023 | 54 | 2023 |
| Graph neural networks: a review of methods and applications. AI Open 1, 57–81 (2020) J Zhou, G Cui, S Hu, Z Zhang, C Yang, Z Liu, L Wang, C Li, M Sun Prompt used to predict future trend (Table 12 and 13)–Prompt used to …, 1812 | 53 | 1812 |
| & Sun, M.(2020) J Zhou, G Cui, S Hu, Z Zhang, C Yang, Z Liu Graph neural networks: A review of methods and applications. AI open 1, 57-81, 0 | 52 | |
| Copen: Probing conceptual knowledge in pre-trained language models H Peng, X Wang, S Hu, H Jin, L Hou, J Li, Z Liu, Q Liu arXiv preprint arXiv:2211.04079, 2022 | 46 | 2022 |
| Sparse structure search for delta tuning S Hu, Z Zhang, N Ding, Y Wang, Y Wang, Z Liu, M Sun Advances in Neural Information Processing Systems, 2022 | 32* | 2022 |
| Prosparse: Introducing and enhancing intrinsic activation sparsity within large language models C Song, X Han, Z Zhang, S Hu, X Shi, K Li, C Chen, Z Liu, G Li, T Yang, ... arXiv preprint arXiv:2402.13516, 2024 | 24 | 2024 |
| Won't get fooled again: Answering questions with false premises S Hu, Y Luo, H Wang, X Cheng, Z Liu, M Sun arXiv preprint arXiv:2307.02394, 2023 | 15 | 2023 |
Zhiyuan LiuAssociate Professor, Tsinghua University確認したメール アドレス: tsinghua.edu.cn
