| Emotional chatting machine: Emotional conversation generation with internal and external memory H Zhou, M Huang, T Zhang, X Zhu, B Liu Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 896 | 2018 |
| Commonsense knowledge aware conversation generation with graph attention. H Zhou, T Young, M Huang, H Zhao, J Xu, X Zhu IJCAI, 4623-4629, 2018 | 544 | 2018 |
| Augmenting end-to-end dialogue systems with commonsense knowledge T Young, E Cambria, I Chaturvedi, H Zhou, S Biswas, M Huang Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 371 | 2018 |
| KdConv: A Chinese multi-domain dialogue dataset towards multi-turn knowledge-driven conversation H Zhou, C Zheng, K Huang, M Huang, X Zhu arXiv preprint arXiv:2004.04100, 2020 | 112 | 2020 |
| CPM: A large-scale generative Chinese pre-trained language model Z Zhang, X Han, H Zhou, P Ke, Y Gu, D Ye, Y Qin, Y Su, H Ji, J Guan, F Qi, ... AI Open 2, 93-99, 2021 | 110 | 2021 |
| Large language models are not robust multiple choice selectors C Zheng, H Zhou, F Meng, J Zhou, M Huang The Twelfth International Conference on Learning Representations, 2023 | 72 | 2023 |
| On the safety of conversational models: Taxonomy, dataset, and benchmark H Sun, G Xu, J Deng, J Cheng, C Zheng, H Zhou, N Peng, X Zhu, ... arXiv preprint arXiv:2110.08466, 2021 | 65 | 2021 |
| Label words are anchors: An information flow perspective for understanding in-context learning L Wang, L Li, D Dai, D Chen, H Zhou, F Meng, J Zhou, X Sun arXiv preprint arXiv:2305.14160, 2023 | 63 | 2023 |
| Eva: An open-domain chinese dialogue system with large-scale generative pre-training H Zhou, P Ke, Z Zhang, Y Gu, Y Zheng, C Zheng, Y Wang, CH Wu, H Sun, ... arXiv preprint arXiv:2108.01547, 2021 | 44 | 2021 |
| Context-aware natural language generation for spoken dialogue systems H Zhou, M Huang, X Zhu Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 37 | 2016 |
| On Large Language Models' Selection Bias in Multi-Choice Questions C Zheng, H Zhou, F Meng, J Zhou, M Huang arXiv preprint arXiv:2309.03882, 2023 | 31 | 2023 |
| Towards codable text watermarking for large language models L Wang, W Yang, D Chen, H Zhou, Y Lin, F Meng, J Zhou, X Sun arXiv preprint arXiv:2307.15992, 2023 | 30 | 2023 |
| CTRLEval: An unsupervised reference-free metric for evaluating controlled text generation P Ke, H Zhou, Y Lin, P Li, J Zhou, X Zhu, M Huang arXiv preprint arXiv:2204.00862, 2022 | 29 | 2022 |
| Prompt-driven llm safeguarding via directed representation optimization C Zheng, F Yin, H Zhou, F Meng, J Zhou, KW Chang, M Huang, N Peng arXiv preprint arXiv:2401.18018, 2024 | 18 | 2024 |
| Domain-constrained advertising keyword generation H Zhou, M Huang, Y Mao, C Zhu, P Shu, X Zhu The World Wide Web Conference, 2448-2459, 2019 | 18 | 2019 |
| EARL: informative knowledge-grounded conversation generation with entity-agnostic representation learning H Zhou, M Huang, Y Liu, W Chen, X Zhu Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 11 | 2021 |
| Recall: A benchmark for llms robustness against external counterfactual knowledge Y Liu, L Huang, S Li, S Chen, H Zhou, F Meng, J Zhou, X Sun arXiv preprint arXiv:2311.08147, 2023 | 7 | 2023 |
| Integrating local real data with global gradient prototypes for classifier re-balancing in federated long-tailed learning W Yang, D Chen, H Zhou, F Meng, J Zhou, X Sun arXiv preprint arXiv:2301.10394, 2023 | 7 | 2023 |
| Rose: Robust selective fine-tuning for pre-trained language models L Jiang, H Zhou, Y Lin, P Li, J Zhou, R Jiang arXiv preprint arXiv:2210.09658, 2022 | 6 | 2022 |
| Diffusion theory as a scalpel: Detecting and purifying poisonous dimensions in pre-trained language models caused by backdoor or bias Z Zhang, D Chen, H Zhou, F Meng, J Zhou, X Sun arXiv preprint arXiv:2305.04547, 2023 | 5 | 2023 |
Xiaoyan ZhuTsinghua UniversityZweryfikowany adres z tsinghua.edu.cn
