Codegen: An open large language model for code with multi-turn program synthesis E Nijkamp, B Pang, H Hayashi, L Tu, H Wang, Y Zhou, S Savarese, ... arXiv preprint arXiv:2203.13474, 2022 | 529 | 2022 |
Deep learning with tensorflow: A review B Pang, E Nijkamp, YN Wu Journal of Educational and Behavioral Statistics 45 (2), 227-248, 2020 | 325 | 2020 |
A conversational paradigm for program synthesis E Nijkamp, B Pang, H Hayashi, L Tu, H Wang, Y Zhou, S Savarese, ... arXiv preprint arXiv:2203.13474 30, 2022 | 128 | 2022 |
Learning latent space energy-based prior model B Pang, T Han, E Nijkamp, SC Zhu, YN Wu NeurIPS 2020, 2020 | 122 | 2020 |
Trajectory Prediction with Latent Belief Energy-Based Model B Pang, T Zhao, X Xie, YN Wu CVPR 2021, 11814-11824, 2021 | 76 | 2021 |
Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation B Pang, E Nijkamp, W Han, L Zhou, Y Liu, K Tu ACL 2020, 2020 | 74 | 2020 |
Robust Transfer Learning with Pretrained Language Models through Adapters W Han*, B Pang*, Y Wu ACL 2021, 2021 | 52 | 2021 |
Latent diffusion energy-based model for interpretable text modeling P Yu, S Xie, X Ma, B Jia, B Pang, R Gao, Y Zhu, SC Zhu, YN Wu arXiv preprint arXiv:2206.05895, 2022 | 50 | 2022 |
Learning multi-layer latent variable model via variational optimization of short run MCMC for approximate inference E Nijkamp*, B Pang*, T Han, L Zhou, SC Zhu, YN Wu ECCV 2020, 2020 | 46 | 2020 |
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model T Han, E Nijkamp, L Zhou, B Pang, SC Zhu, YN Wu CVPR 2020, 7978-7987, 2020 | 42 | 2020 |
Long document summarization with top-down and bottom-up inference B Pang, E Nijkamp, W Kryściński, S Savarese, Y Zhou, C Xiong arXiv preprint arXiv:2203.07586, 2022 | 36 | 2022 |
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification B Pang, YN Wu ICML 2021, 8359-8370, 2021 | 22 | 2021 |
Learning energy-based model with flow-based backbone by neural transport mcmc E Nijkamp, R Gao, P Sountsov, S Vasudevan, B Pang, SC Zhu, YN Wu arXiv preprint arXiv:2006.06897 1 (2), 2020 | 21 | 2020 |
Mcmc should mix: Learning energy-based model with neural transport latent space mcmc E Nijkamp, R Gao, P Sountsov, S Vasudevan, B Pang, SC Zhu, YN Wu arXiv preprint arXiv:2006.06897, 2020 | 20 | 2020 |
Artificial modification on lateral hydrological connectivity promotes range expansion of invasive Spartina alterniflora in salt marshes of the Yellow River delta, China T Xie, Q Wang, Z Ning, C Chen, B Cui, J Bai, W Shi, B Pang Science of the Total Environment 769, 144476, 2021 | 15 | 2021 |
Long sequence modeling with xgen: A 7b llm trained on 8k input sequence length E Nijkamp, T Xie, H Hayashi, B Pang, C Xia, C Xing, J Vig, S Yavuz, ... Salesforce AI Research Blog, 2023 | 13 | 2023 |
Learning Latent Space Energy-Based Prior Model for Molecule Generation B Pang, T Han, YN Wu NeurIPS Workshop 2020, 2020 | 10 | 2020 |
Xgen-7b technical report E Nijkamp, T Xie, H Hayashi, B Pang, C Xia, C Xing, J Vig, S Yavuz, ... arXiv preprint arXiv:2309.03450, 2023 | 8 | 2023 |
Learning probabilistic models from generator latent spaces with hat ebm M Hill, E Nijkamp, J Mitchell, B Pang, SC Zhu Advances in Neural Information Processing Systems 35, 928-940, 2022 | 7 | 2022 |
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling B Pang, E Nijkamp, J Cui, T Han, YN Wu NeurIPS Workshop 2020, 2020 | 7 | 2020 |