| Template-free prompt tuning for few-shot NER R Ma*, X Zhou*, T Gui, Y Tan, L Li, Q Zhang, X Huang arXiv preprint arXiv:2109.13532, 2021 | 164 | 2021 |
| Textflint: Unified multilingual robustness evaluation toolkit for natural language processing X Wang, Q Liu, T Gui, Q Zhang, Y Zou, X Zhou, J Ye, Y Zhang, R Zheng, ... Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 121* | 2021 |
| Coarse-to-fine few-shot learning for named entity recognition R Ma, Z Lin, X Chen, X Zhou, J Wang, T Gui, Q Zhang, X Gao, YW Chen Findings of the Association for Computational Linguistics: ACL 2023, 4115-4129, 2023 | 13 | 2023 |
| Making harmful behaviors unlearnable for large language models X Zhou, Y Lu, R Ma, T Gui, Q Zhang, X Huang arXiv preprint arXiv:2311.02105, 2023 | 12 | 2023 |
| Textobfuscator: Making pre-trained language model a privacy protector via obfuscating word representations X Zhou, Y Lu, R Ma, T Gui, Y Wang, Y Ding, Y Zhang, Q Zhang, XJ Huang Findings of the Association for Computational Linguistics: ACL 2023, 5459-5473, 2023 | 12 | 2023 |
| Searching for optimal subword tokenization in cross-domain ner R Ma, Y Tan, X Zhou, X Chen, D Liang, S Wang, W Wu, T Gui, Q Zhang arXiv preprint arXiv:2206.03352, 2022 | 12 | 2022 |
| Are Large Language Models Good Prompt Optimizers? R Ma, X Wang, X Zhou, J Li, N Du, T Gui, Q Zhang, X Huang arXiv preprint arXiv:2402.02101, 2024 | 10 | 2024 |
| Textfusion: Privacy-preserving pre-trained model inference via token fusion X Zhou, J Lu, T Gui, R Ma, Z Fei, Y Wang, Y Ding, Y Cheung, Q Zhang, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 10 | 2022 |
| Making parameter-efficient tuning more efficient: A unified framework for classification tasks X Zhou, R Ma, Y Zou, X Chen, T Gui, Q Zhang, XJ Huang, R Xie, W Wu Proceedings of the 29th International Conference on Computational …, 2022 | 9 | 2022 |
| Learning “O” helps for learning more: Handling the unlabeled entity problem for class-incremental NER R Ma, X Chen, Z Lin, X Zhou, J Wang, T Gui, Q Zhang, X Gao, YW Chen Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 6 | 2023 |
| LongHeads: Multi-Head Attention is Secretly a Long Context Processor Y Lu*, X Zhou*, W He, J Zhao, T Ji, T Gui, Q Zhang, X Huang arXiv preprint arXiv:2402.10685, 2024 | 4 | 2024 |
| LFKQG: A controlled generation framework with local fine-tuning for question generation over knowledge bases Z Fei, X Zhou, T Gui, Q Zhang, XJ Huang Proceedings of the 29th International Conference on Computational …, 2022 | 4 | 2022 |
| Towards building more robust ner datasets: An empirical study on ner dataset bias from a dataset difficulty view R Ma, X Wang, X Zhou, Q Zhang, XJ Huang Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 2 | 2023 |
| TextMixer: Mixing Multiple Inputs for Privacy-Preserving Inference X Zhou, Y Lu, R Ma, T Gui, Q Zhang, XJ Huang Findings of the Association for Computational Linguistics: EMNLP 2023, 3749-3762, 2023 | 2 | 2023 |
| Plug-tagger: A pluggable sequence labeling framework using language models X Zhou, R Ma, T Gui, Y Tan, Q Zhang, X Huang arXiv preprint arXiv:2110.07331, 2021 | 2 | 2021 |
| ProofInfer: Generating Proof via Iterative Hierarchical Inference Z Fei, Q Zhang, X Zhou, T Gui, XJ Huang Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 1 | 2022 |
