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Baolin Peng
Baolin Peng
Microsoft Research, Redmond
Verified email at microsoft.com
Title
Cited by
Cited by
Year
Instruction tuning with gpt-4
B Peng, C Li, P He, M Galley, J Gao
arXiv preprint arXiv:2304.03277, 2023
7302023
An introduction to computational networks and the computational network toolkit
D Yu, A Eversole, M Seltzer, K Yao, Z Huang, B Guenter, O Kuchaiev, ...
Microsoft Technical Report MSR-TR-2014–112, 2014
4752014
Spoken language understanding using long short-term memory neural networks
K Yao, B Peng, Y Zhang, D Yu, G Zweig, Y Shi
2014 IEEE spoken language technology workshop (SLT), 189-194, 2014
4092014
Check your facts and try again: Improving large language models with external knowledge and automated feedback
B Peng, M Galley, P He, H Cheng, Y Xie, Y Hu, Q Huang, L Liden, Z Yu, ...
arXiv preprint arXiv:2302.12813, 2023
3712023
Chameleon: Plug-and-play compositional reasoning with large language models
P Lu, B Peng, H Cheng, M Galley, KW Chang, YN Wu, SC Zhu, J Gao
NeurIPS 2023, 2023
3272023
Soloist: Building Task Bots at Scale with Transfer Learning and Machine Teaching
B Peng, C Li, J Li, S Shayandeh, L Liden, J Gao
Transactions of the Association for Computational Linguistics 9, 807-824, 2021
323*2021
Composite task-completion dialogue policy learning via hierarchical deep reinforcement learning
B Peng, X Li, L Li, J Gao, A Celikyilmaz, S Lee, KF Wong
EMNLP 2017, 2017
2402017
Deep dyna-q: Integrating planning for task-completion dialogue policy learning
B Peng, X Li, J Gao, J Liu, KF Wong
ACL 2018, 2018
2382018
Task-oriented dialogue system for automatic diagnosis
Z Wei, Q Liu, B Peng, H Tou, T Chen, XJ Huang, KF Wong, X Dai
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
2322018
Few-shot natural language generation for task-oriented dialog
B Peng, C Zhu, C Li, X Li, J Li, M Zeng, J Gao
EMNLP 2020, 2020
2192020
Optimus: Organizing sentences via pre-trained modeling of a latent space
C Li, X Gao, Y Li, B Peng, X Li, Y Zhang, J Gao
EMNLP 2020, 2020
1832020
Recurrent conditional random field for language understanding
K Yao, B Peng, G Zweig, D Yu, X Li, F Gao
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
1652014
Attention with intention for a neural network conversation model
K Yao, G Zweig, B Peng
arXiv preprint arXiv:1510.08565, 2015
1452015
Convlab-2: An open-source toolkit for building, evaluating, and diagnosing dialogue systems
Q Zhu, Z Zhang, Y Fang, X Li, R Takanobu, J Li, B Peng, J Gao, X Zhu, ...
arXiv preprint arXiv:2002.04793, 2020
1282020
Convlab: Multi-domain end-to-end dialog system platform
S Lee, Q Zhu, R Takanobu, X Li, Y Zhang, Z Zhang, J Li, B Peng, X Li, ...
arXiv preprint arXiv:1904.08637, 2019
1122019
Explanations from large language models make small reasoners better
S Li, J Chen, Y Shen, Z Chen, X Zhang, Z Li, H Wang, J Qian, B Peng, ...
arXiv preprint arXiv:2210.06726, 2022
1112022
Few-shot named entity recognition: An empirical baseline study
J Huang, C Li, K Subudhi, D Jose, S Balakrishnan, W Chen, B Peng, ...
Proceedings of the 2021 conference on empirical methods in natural language …, 2021
982021
Recurrent neural networks with external memory for spoken language understanding
B Peng, K Yao, L Jing, KF Wong
Natural Language Processing and Chinese Computing: 4th CCF Conference, NLPCC …, 2015
972015
Towards neural network-based reasoning
B Peng, Z Lu, H Li, KF Wong
arXiv preprint arXiv:1508.05508, 2015
942015
Contextual spoken language understanding using recurrent neural networks
Y Shi, K Yao, H Chen, YC Pan, MY Hwang, B Peng
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
922015
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Articles 1–20