| Generative pretraining in multimodality Q Sun*, Q Yu*, Y Cui*, F Zhang*, X Zhang*, Y Wang, H Gao, J Liu, ... ICLR, 2024 | 116 | 2024 |
| Exploring the universal vulnerability of prompt-based learning paradigm L Xu, Y Chen, G Cui, H Gao, Z Liu Findings of NAACL, 2022 | 58 | 2022 |
| Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations L Yuan, Y Chen, G Cui, H Gao, F Zou, X Cheng, H Ji, Z Liu, M Sun NeurIPS (Dataset and Benchmark Track) 36, 2023 | 34 | 2023 |
| Why should adversarial perturbations be imperceptible? rethink the research paradigm in adversarial NLP Y Chen*, H Gao*, G Cui, F Qi, L Huang, Z Liu, M Sun EMNLP, 2022 | 28 | 2022 |
| Efficient detection of LLM-generated texts with a Bayesian surrogate model Y Miao*, H Gao*, H Zhang, Z Deng Findings of ACL, 2024 | 11* | 2024 |
| Textual backdoor attacks can be more harmful via two simple tricks Y Chen*, F Qi*, H Gao, Z Liu, M Sun EMNLP, 2022 | 11 | 2022 |
| Evaluating the robustness of text-to-image diffusion models against real-world attacks H Gao, H Zhang, Y Dong, Z Deng arXiv preprint arXiv:2306.13103, 2023 | 9 | 2023 |
| From adversarial arms race to model-centric evaluation: Motivating a unified automatic robustness evaluation framework Y Chen*, H Gao*, G Cui*, L Yuan, D Kong, H Wu, N Shi, B Yuan, L Huang, ... Findings of ACL, 2023 | 5 | 2023 |
| Universal Prompt Optimizer for Safe Text-to-Image Generation Z Wu*, H Gao*, Y Wang, X Zhang, S Wang NAACL, 2024 | 2 | 2024 |
| AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models Z Zeng*, Y Miao*, H Gao, H Zhang, Z Deng arXiv preprint arXiv:2406.13233, 2024 | | 2024 |
| Adaptive Token Biaser: Knowledge Editing via Biasing Key Entities B Bi, S Liu, Y Wang, L Mei, H Gao, Y Xu, X Cheng arXiv preprint arXiv:2406.12468, 2024 | | 2024 |
Zhiyuan LiuAssociate Professor, Tsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
