Bo Pang

According to our database, Bo Pang authored at least 32 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents.

Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, Rithesh Murthy, Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong

CoRR, 2024

RLHF Workflow: From Reward Modeling to Online RLHF.

Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang

CoRR, 2024

Latent Plan Transformer: Planning as Latent Variable Inference.

Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu

CoRR, 2024

ARM: Alignment with Residual Energy-Based Model.

Bo Pang, Caiming Xiong, Yingbo Zhou

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

XGen-7B Technical Report.

Erik Nijkamp, Tian Xie, Hiroaki Hayashi, Bo Pang, Congying Xia, Chen Xing, Jesse Vig, Semih Yavuz, Philippe Laban, Ben Krause, Senthil Purushwalkam, Tong Niu, Wojciech Kryscinski, Lidiya Murakhovs'ka, Prafulla Kumar Choubey, Alexander R. Fabbri, Ye Liu, Rui Meng, Lifu Tu, Meghana Bhat, Chien-Sheng Wu, Silvio Savarese, Yingbo Zhou, Shafiq Joty, Caiming Xiong

CoRR, 2023

Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting.

Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference.

Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu

Proceedings of the International Conference on Machine Learning, 2023

CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Few-shot Unified Question Answering: Tuning Models or Prompts?

Srijan Bansal, Semih Yavuz, Bo Pang, Meghana Bhat, Yingbo Zhou

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SharPT: Shared Latent Space Prompt Tuning.

Bo Pang, Semih Yavuz, Caiming Xiong, Yingbo Zhou

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Long Document Summarization with Top-down and Bottom-up Inference.

Bo Pang, Erik Nijkamp, Wojciech Kryscinski, Silvio Savarese, Yingbo Zhou, Caiming Xiong

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

2022

BigIssue: A Realistic Bug Localization Benchmark.

Paul Kassianik, Erik Nijkamp, Bo Pang, Yingbo Zhou, Caiming Xiong

CoRR, 2022

Latent Diffusion Energy-Based Model for Interpretable Text Modeling.

Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu

CoRR, 2022

A Conversational Paradigm for Program Synthesis.

Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong

CoRR, 2022

Learning Probabilistic Models from Generator Latent Spaces with Hat EBM.

Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Latent Diffusion Energy-Based Model for Interpretable Text Modelling.

Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu

Proceedings of the International Conference on Machine Learning, 2022

MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC.

Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

SCRIPT: Self-Critic PreTraining of Transformers.

Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification.

Bo Pang, Ying Nian Wu

Proceedings of the 38th International Conference on Machine Learning, 2021

Generative Text Modeling through Short Run Inference.

Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Trajectory Prediction With Latent Belief Energy-Based Model.

Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Robust Transfer Learning with Pretrained Language Models through Adapters.

Wenjuan Han, Bo Pang, Ying Nian Wu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling.

Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

CoRR, 2020

Learning Latent Space Energy-Based Prior Model for Molecule Generation.

Bo Pang, Tian Han, Ying Nian Wu

CoRR, 2020

Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC.

Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu

CoRR, 2020

Learning Latent Space Energy-Based Prior Model.

Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference.

Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Computer Vision - ECCV 2020, 2020

Joint Training of Variational Auto-Encoder and Latent Energy-Based Model.

Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation.

Bo Pang, Erik Nijkamp, Wenjuan Han, Linqi Zhou, Yixian Liu, Kewei Tu

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Learning Deep Generative Models with Short Run Inference Dynamics.

Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu

CoRR, 2019

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases.

Tao Yu, Rui Zhang, Heyang Er, Suyi Li, Eric Xue, Bo Pang, Xi Victoria Lin, Yi Chern Tan, Tianze Shi, Zihan Li, Youxuan Jiang, Michihiro Yasunaga, Sungrok Shim, Tao Chen, Alexander R. Fabbri, Zifan Li, Luyao Chen, Yuwen Zhang, Shreya Dixit, Vincent Zhang, Caiming Xiong, Richard Socher, Walter S. Lasecki, Dragomir R. Radev

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

SParC: Cross-Domain Semantic Parsing in Context.

Tao Yu, Rui Zhang, Michihiro Yasunaga, Yi Chern Tan, Xi Victoria Lin, Suyi Li, Heyang Er, Irene Li, Bo Pang, Tao Chen, Emily Ji, Shreya Dixit, David Proctor, Sungrok Shim, Jonathan Kraft, Vincent Zhang, Caiming Xiong, Richard Socher, Dragomir R. Radev

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019