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2020 – today
- 2023
[i32]Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao:
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR abs/2302.09632 (2023)- [i31]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. CoRR abs/2304.13712 (2023) - [i30]Jie Huang, Yifan Gao, Zheng Li, Jingfeng Yang, Yangqiu Song, Chao Zhang, Zining Zhu, Haoming Jiang, Kevin Chen-Chuan Chang, Bing Yin:
CCGen: Explainable Complementary Concept Generation in E-Commerce. CoRR abs/2305.11480 (2023) - 2022
- [c30]Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang:
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. ACL (1) 2022: 474-485 - [c29]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. ICLR 2022 - [c28]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin:
Condensing Graphs via One-Step Gradient Matching. KDD 2022: 720-730 - [c27]Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang:
AutoGDA: Automated Graph Data Augmentation for Node Classification. LoG 2022: 32 - [c26]Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang:
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models. NAACL-HLT (Findings) 2022: 49-60 - [c25]Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha:
Self-Training with Differentiable Teacher. NAACL-HLT (Findings) 2022: 933-949 - [c24]Chen Luo, William Headden, Neela Avudaiappan, Haoming Jiang, Tianyu Cao, Qingyu Yin, Yifan Gao, Zheng Li, Rahul Goutam, Haiyang Zhang, Bing Yin:
Query Attribute Recommendation at Amazon Search. RecSys 2022: 506-508 - [i29]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR abs/2202.02664 (2022) - [i28]Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang:
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. CoRR abs/2203.14987 (2022) - [i27]Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang:
SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models. CoRR abs/2205.07381 (2022) - [i26]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying:
Condensing Graphs via One-Step Gradient Matching. CoRR abs/2206.07746 (2022) - [i25]Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao:
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR abs/2209.07499 (2022) - [i24]Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao:
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. CoRR abs/2209.07584 (2022) - [i23]Haoming Jiang, Tianyu Cao, Zheng Li, Chen Luo, Xianfeng Tang, Qingyu Yin, Danqing Zhang, Rahul Goutam, Bing Yin:
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding. CoRR abs/2210.03915 (2022) - 2021
- [b1]Haoming Jiang:
Reducing Human Labor Cost in Deep Learning for Natural Language Processing. Georgia Institute of Technology, Atlanta, GA, USA, 2021 - [c23]Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao:
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. ACL/IJCNLP (1) 2021: 1775-1789 - [c22]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) 2021: 6524-6538 - [c21]Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao:
Learning to Defend by Learning to Attack. AISTATS 2021: 577-585 - [c20]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. EMNLP (Findings) 2021: 3658-3670 - [c19]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. EMNLP (Findings) 2021: 4118-4131 - [c18]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. EMNLP (1) 2021: 6562-6577 - [c17]Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei:
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) 2021: 7419-7451 - [c16]Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang:
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. NAACL-HLT 2021: 1063-1077 - [i22]Haoming Jiang, Bo Dai, Mengjiao Yang, Wei Wei, Tuo Zhao:
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. CoRR abs/2102.10242 (2021) - [i21]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. CoRR abs/2103.11088 (2021) - [i20]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. CoRR abs/2104.04886 (2021) - [i19]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR abs/2105.12002 (2021) - [i18]Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao:
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. CoRR abs/2106.08977 (2021) - [i17]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. CoRR abs/2109.07048 (2021) - [i16]Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha:
Self-Training with Differentiable Teacher. CoRR abs/2109.07049 (2021) - 2020
- [c15]Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao:
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. ACL 2020: 1823-1834 - [c14]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu
, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. ACL 2020: 2177-2190 - [c13]Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang:
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. EMNLP (1) 2020: 1326-1340 - [c12]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. ICLR 2020 - [c11]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Robust and Smooth Policy. ICML 2020: 8707-8718 - [c10]Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha:
Transformer Hawkes Process. ICML 2020: 11692-11702 - [c9]Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. KDD 2020: 1054-1064 - [i15]Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha:
Transformer Hawkes Process. CoRR abs/2002.09291 (2020) - [i14]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Smooth Policy. CoRR abs/2003.09534 (2020) - [i13]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR abs/2006.15261 (2020) - [i12]Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. CoRR abs/2006.15509 (2020) - [i11]Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang:
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. CoRR abs/2010.07835 (2020) - [i10]Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang:
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. CoRR abs/2010.11506 (2020)
2010 – 2019
- 2019
- [j2]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. 20: 44:1-44:5 (2019) - [j1]Xuejin Chen, Haoming Jiang, Tingting Xuan, Lihan Huang, Ligang Liu:
Designing deployable 3D scissor structures with ball-and-socket joints. Comput. Animat. Virtual Worlds 30(1) (2019) - [c8]Yifu Sun, Haoming Jiang:
Contextual Text Denoising with Masked Language Model. W-NUT@EMNLP 2019: 286-290 - [c7]Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao:
Learning to Defense by Learning to Attack. DGS@ICLR 2019 - [c6]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. ICLR (Poster) 2019 - [c5]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. DGS@ICLR 2019 - [c4]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. ICML 2019: 6882-6892 - [c3]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. NeurIPS 2019: 8172-8182 - [c2]Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha:
Meta Learning with Relational Information for Short Sequences. NeurIPS 2019: 9901-9912 - [c1]Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI 2019: 49-59 - [i9]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. CoRR abs/1905.00158 (2019) - [i8]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. CoRR abs/1908.01842 (2019) - [i7]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. CoRR abs/1908.03265 (2019) - [i6]Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha:
Meta Learning with Relational Information for Short Sequences. CoRR abs/1909.02105 (2019) - [i5]Yifu Sun, Haoming Jiang:
Contextual Text Denoising with Masked Language Models. CoRR abs/1910.14080 (2019) - [i4]Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao:
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. CoRR abs/1911.02692 (2019) - [i3]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. CoRR abs/1911.03437 (2019) - 2018
- [i2]Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao:
Learning to Defense by Learning to Attack. CoRR abs/1811.01213 (2018) - [i1]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of GANs with Spectrum Control. CoRR abs/1812.10912 (2018)
Coauthor Index
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last updated on 2023-05-28 01:23 CEST by the dblp team
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