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ORCIDHaoli Bai
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2020 – today
- 2024
[c20]Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan:
IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact. ACL (Findings) 2024: 7716-7741- [c19]Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Surr:
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric. CVPR 2024: 27360-27370 - [c18]Yingtao Zhang, Haoli Bai, Haokun Lin, Jialin Zhao, Lu Hou, Carlo Vittorio Cannistraci:
Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models. ICLR 2024 - [c17]Zhiming Mao, Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Kam-Fai Wong:
Visually Guided Generative Text-Layout Pre-training for Document Intelligence. NAACL-HLT 2024: 4713-4730 - [i17]Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan:
IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact. CoRR abs/2403.01241 (2024) - [i16]Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun:
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric. CoRR abs/2403.07839 (2024) - [i15]Zhiming Mao, Haoli Bai, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu, Kam-Fai Wong:
Visually Guided Generative Text-Layout Pre-training for Document Intelligence. CoRR abs/2403.16516 (2024) - [i14]Parsa Kavehzadeh, Mohammadreza Pourreza, Mojtaba Valipour, Tinashu Zhu, Haoli Bai, Ali Ghodsi, Boxing Chen, Mehdi Rezagholizadeh:
S2D: Sorted Speculative Decoding For More Efficient Deployment of Nested Large Language Models. CoRR abs/2407.01955 (2024) - [i13]Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao:
FlatQuant: Flatness Matters for LLM Quantization. CoRR abs/2410.09426 (2024) - 2023
- [c16]Chaofan Tao, Lu Hou, Haoli Bai, Jiansheng Wei, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong:
Structured Pruning for Efficient Generative Pre-trained Language Models. ACL (Findings) 2023: 10880-10895 - [c15]Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Yifeng Luo, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu:
Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding. ACL (1) 2023: 13386-13401 - 2022
- [c14]Haoli Bai, Hongda Mao, Dinesh Nair:
Dynamically Pruning Segformer for Efficient Semantic Segmentation. ICASSP 2022: 3298-3302 - [c13]Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu:
Towards Efficient Post-training Quantization of Pre-trained Language Models. NeurIPS 2022 - [i12]Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu:
Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding. CoRR abs/2212.09621 (2022) - 2021
- [j5]Liangjian Wen, Haoli Bai, Lirong He, Yiji Zhou, Mingyuan Zhou
, Zenglin Xu:
Gradient estimation of information measures in deep learning. Knowl. Based Syst. 224: 107046 (2021) - [c12]Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jin Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King:
BinaryBERT: Pushing the Limit of BERT Quantization. ACL/IJCNLP (1) 2021: 4334-4348 - [c11]Chung-Yiu Yau, Haoli Bai, Irwin King, Michael R. Lyu:
DAP-BERT: Differentiable Architecture Pruning of BERT. ICONIP (1) 2021: 367-378 - [c10]Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King:
Discrete Auto-regressive Variational Attention Models for Text Modeling. IJCNN 2021: 1-8 - [i11]Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King:
Discrete Auto-regressive Variational Attention Models for Text Modeling. CoRR abs/2106.08571 (2021) - [i10]Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu:
Towards Efficient Post-training Quantization of Pre-trained Language Models. CoRR abs/2109.15082 (2021) - [i9]Haoli Bai, Hongda Mao, Dinesh Nair:
Dynamically pruning segformer for efficient semantic segmentation. CoRR abs/2111.09499 (2021) - 2020
- [j4]Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Jian Cheng:
Bayesian Automatic Model Compression. IEEE J. Sel. Top. Signal Process. 14(4): 727-736 (2020) - [j3]Liangjian Wen, Xuanyang Zhang, Haoli Bai, Zenglin Xu:
Structured pruning of recurrent neural networks through neuron selection. Neural Networks 123: 134-141 (2020) - [j2]Xianghong Fang, Haoli Bai, Ziyi Guo, Bin Shen, Steven C. H. Hoi, Zenglin Xu:
DART: Domain-Adversarial Residual-Transfer networks for unsupervised cross-domain image classification. Neural Networks 127: 182-192 (2020) - [c9]Haoli Bai, Jiaxiang Wu, Irwin King, Michael R. Lyu:
Few Shot Network Compression via Cross Distillation. AAAI 2020: 3203-3210 - [c8]Yuhang Li, Xin Dong, Sai Qian Zhang, Haoli Bai, Yuanpeng Chen, Wei Wang:
RTN: Reparameterized Ternary Network. AAAI 2020: 4780-4787 - [c7]Jiaxing Wang, Jiaxiang Wu, Haoli Bai, Jian Cheng:
M-NAS: Meta Neural Architecture Search. AAAI 2020: 6186-6193 - [c6]Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai, Junzhou Huang:
TranSlider: Transfer Ensemble Learning from Exploitation to Exploration. KDD 2020: 368-378 - [c5]Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael R. Lyu, Jian Cheng:
Revisiting Parameter Sharing for Automatic Neural Channel Number Search. NeurIPS 2020 - [i8]Yuhang Li, Wei Wang, Haoli Bai, Ruihao Gong, Xin Dong, Fengwei Yu:
Efficient Bitwidth Search for Practical Mixed Precision Neural Network. CoRR abs/2003.07577 (2020) - [i7]Xianghong Fang, Haoli Bai, Zenglin Xu, Michael R. Lyu, Irwin King:
Discrete Variational Attention Models for Language Generation. CoRR abs/2004.09764 (2020) - [i6]Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jing Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King:
BinaryBERT: Pushing the Limit of BERT Quantization. CoRR abs/2012.15701 (2020)
2010 – 2019
- 2019
- [j1]Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville:
Variational Random Function Model for Network Modeling. IEEE Trans. Neural Networks Learn. Syst. 30(1): 318-324 (2019) - [i5]Liangjiang Wen, Xueyang Zhang, Haoli Bai, Zenglin Xu:
Structured Pruning of Recurrent Neural Networks through Neuron Selection. CoRR abs/1906.06847 (2019) - [i4]Haoli Bai, Jiaxiang Wu, Irwin King, Michael R. Lyu:
Few Shot Network Compression via Cross Distillation. CoRR abs/1911.09450 (2019) - [i3]Yuhang Li, Xin Dong, Sai Qian Zhang, Haoli Bai, Yuanpeng Chen, Wei Wang:
RTN: Reparameterized Ternary Network. CoRR abs/1912.02057 (2019) - 2018
- [c4]Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu:
Neural Relational Topic Models for Scientific Article Analysis. CIKM 2018: 27-36 - [c3]Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu:
Structured Inference for Recurrent Hidden Semi-markov Model. IJCAI 2018: 2447-2453 - [i2]Xianghong Fang, Haoli Bai, Ziyi Guo, Bin Shen, Steven C. H. Hoi, Zenglin Xu:
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification. CoRR abs/1812.11478 (2018) - 2017
- [c2]Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe:
Learning from semantically dependent multi-tasks. IJCNN 2017: 3498-3505 - [i1]Hao Liu, Haoli Bai, Lirong He, Zenglin Xu:
Stochastic Sequential Neural Networks with Structured Inference. CoRR abs/1705.08695 (2017) - 2016
- [c1]Haoli Bai, Zenglin Xu, Bin Liu, Yingming Li:
Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network. ACML 2016: 270-285
Coauthor Index
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