| Temporal models for predicting student dropout in massive open online courses M Fei, DY Yeung 2015 IEEE international conference on data mining workshop (ICDMW), 256-263, 2015 | 336 | 2015 |
| Aligning large language models with human: A survey Y Wang, W Zhong, L Li, F Mi, X Zeng, W Huang, L Shang, X Jiang, Q Liu arXiv preprint arXiv:2307.12966, 2023 | 291 | 2023 |
| Syncobert: Syntax-guided multi-modal contrastive pre-training for code representation X Wang, Y Wang, F Mi, P Zhou, Y Wan, X Liu, L Li, H Wu, J Liu, X Jiang arXiv preprint arXiv:2108.04556, 2021 | 126 | 2021 |
| Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems F Mi, M Huang, J Zhang, B Faltings IJCAI 2019, 2019 | 115 | 2019 |
| Personalization in goal-oriented dialog CK Joshi, F Mi, B Faltings NeurIPS Conversational AI Workshop, 2017 | 109 | 2017 |
| Masking as an Efficient Alternative to Finetuning for Pretrained Language Models M Zhao, T Lin, F Mi, M Jaggi, H Schütze EMNLP, 2020 | 108 | 2020 |
| Cold: A benchmark for chinese offensive language detection J Deng, J Zhou, H Sun, F Mi, M Huang EMNLP 2022 Main, 2022 | 94 | 2022 |
| Continual Learning for Natural Language Generation in Task-oriented Dialog Systems F Mi, L Chen, M Zhao, M Huang, B Faltings Findings of EMNLP, 2020 | 72 | 2020 |
| Defending large language models against jailbreaking attacks through goal prioritization Z Zhang, J Yang, P Ke, F Mi, H Wang, M Huang https://arxiv.org/abs/2311.09096, 2024 | 71 | 2024 |
| Continual Prompt Tuning for Dialog State Tracking Q Zhu, B Li, F Mi, X Zhu, M Huang ACL 2022 Main, 2022 | 66 | 2022 |
| ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation F Mi, X Lin, B Faltings The ACM Conference on Recommender Systems (RecSys), 2020, 2020 | 66 | 2020 |
| Compilable Neural Code Generation with Compiler Feedback X Wang, Y Wang, Y Wan, F Mi, Y Li, P Zhou, J Liu, H Wu, X Jiang, Q Liu ACL 2022 Findings, 2022 | 65 | 2022 |
| Cue-CoT: Chain-of-thought prompting for responding to in-depth dialogue questions with LLMs H Wang, R Wang, F Mi, Y Deng, Z Wang, B Liang, R Xu, KF Wong arXiv preprint arXiv:2305.11792, 2023 | 50 | 2023 |
| Probabilistic graphical models for boosting cardinal and ordinal peer grading in MOOCs F Mi, DY Yeung Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 47 | 2015 |
| Generalized class incremental learning F Mi, L Kong, T Lin, K Yu, B Faltings Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 46 | 2020 |
| CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems F Mi, Y Li, Y Wang, X Jiang, Q Liu Accepted at AAAI 2022, 2021 | 41 | 2021 |
| Followbench: A multi-level fine-grained constraints following benchmark for large language models Y Jiang, Y Wang, X Zeng, W Zhong, L Li, F Mi, L Shang, X Jiang, Q Liu, ... arXiv preprint arXiv:2310.20410, 2023 | 37 | 2023 |
| Memory Augmented Neural Model for Incremental Session-based Recommendation F Mi, B Faltings IJCAI 2020, 2020 | 32 | 2020 |
| Data management for large language models: A survey Z Wang, W Zhong, Y Wang, Q Zhu, F Mi, B Wang, L Shang, X Jiang, Q Liu CoRR, 2023 | 27 | 2023 |
| Towards identifying social bias in dialog systems: Framework, dataset, and benchmark J Zhou, J Deng, F Mi, Y Li, Y Wang, M Huang, X Jiang, Q Liu, H Meng Findings of the Association for Computational Linguistics: EMNLP 2022, 3576-3591, 2022 | 27 | 2022 |
Yasheng WangNoah's Ark Lab, HuaweiVerifierad e-postadress på huawei.com