| Template-free prompt tuning for few-shot NER R Ma*, X Zhou*, T Gui, Y Tan, L Li, Q Zhang, X Huang NAACL 2022, 2021 | 193 | 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 | 128* | 2021 |
| 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 | 24 | 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, ... EMNLP 2022, 8360-8371, 2022 | 15 | 2022 |
| Making harmful behaviors unlearnable for large language models X Zhou, Y Lu, R Ma, T Gui, Q Zhang, X Huang ACL 2024 Findings, 2023 | 14 | 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 ACL 2023 Findings, 5459-5473, 2023 | 14 | 2023 |
| 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 ACL 2023 Findings, 4115-4129, 2023 | 14 | 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 IJCAI 2022, 2022 | 13 | 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 ACL 2023, 5959-5979, 2023 | 9 | 2023 |
| 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 COLING 2022, 7053-7064, 2022 | 9 | 2022 |
| 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 EMNLP 2024 Findings, 2024 | 6 | 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 COLING 2022, 6575-6585, 2022 | 6 | 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 EMNLP 2023, 4616-4630, 2023 | 4 | 2023 |
| TextMixer: Mixing Multiple Inputs for Privacy-Preserving Inference X Zhou, Y Lu, R Ma, T Gui, Q Zhang, XJ Huang EMNLP 2023 Findings, 3749-3762, 2023 | 3 | 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 EMNLP 2022, 10883-10892, 2022 | 1 | 2022 |
| Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs X Zhou, P Nie, Y Guo, H Wei, Z Zhang, P Minervini, R Ma, T Gui, Q Zhang, ... EMNLP 2024, 2024 | | 2024 |
