Bosheng Ding
Cited by
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DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks
B Ding, L Liu, L Bing, C Kruengkrai, TH Nguyen, S Joty, L Si, C Miao
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
On the effectiveness of adapter-based tuning for pretrained language model adaptation
R He, L Liu, H Ye, Q Tan, B Ding, L Cheng, JW Low, L Bing, L Si
ACL2021, 2021
MulDA: A multilingual data augmentation framework for low-resource cross-lingual NER
L Liu, B Ding, L Bing, S Joty, L Si, C Miao
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
Globalwoz: Globalizing multiwoz to develop multilingual task-oriented dialogue systems
B Ding, J Hu, L Bing, SM Aljunied, S Joty, L Si, C Miao
ACL2022, 2021
Is GPT-3 a Good Data Annotator?
B Ding, C Qin, L Liu, L Bing, S Joty, B Li
ACL2023, 2022
Retrieving multimodal information for augmented generation: A survey
R Zhao, H Chen, W Wang, F Jiao, XL Do, C Qin, B Ding, X Guo, M Li, X Li, ...
arXiv preprint arXiv:2303.10868, 2023
Can chatgpt-like generative models guarantee factual accuracy? on the mistakes of new generation search engines
R Zhao, X Li, YK Chia, B Ding, L Bing
arXiv preprint arXiv:2304.11076, 2023
LogicLLM: Exploring Self-supervised Logic-enhanced Training for Large Language Models
F Jiao, Z Teng, S Joty, B Ding, A Sun, Z Liu, NF Chen
arXiv preprint arXiv:2305.13718, 2023
Chain of Knowledge: A Framework for Grounding Large Language Models with Structured Knowledge Bases
X Li, R Zhao, YK Chia, B Ding, L Bing, S Joty, S Poria
arXiv preprint arXiv:2305.13269, 2023
Panda LLM: Training Data and Evaluation for Open-Sourced Chinese Instruction-Following Large Language Models
F Jiao, B Ding, T Luo, Z Mo
arXiv preprint arXiv:2305.03025, 2023
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