Haoming Jiang

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 76

Top Topics

Stackelberg Game

Top Venues

Publications

Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. ICLR (2023)
Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR (2023)
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. ACL (industry) (2023)
Karan Samel, Houyu Zhang, Jun Ma, Haoming Jiang, Qing Ping, Sheng Wang, Yi Xu, Belinda Zeng, Trishul Chilimbi
SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce. BigData (2023)
Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin
Graph Reasoning for Question Answering with Triplet Retrieval. CoRR (2023)
Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao
LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. KDD (2023)
Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. CoRR (2023)
Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin
Graph Reasoning for Question Answering with Triplet Retrieval. ACL (Findings) (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS (2023)
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 (2023)
Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, Bing Yin
Situated Natural Language Explanations. CoRR (2023)
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 (2023)
Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. ICML (2023)
Hui Liu, Qingyu Yin, Zhengyang Wang, Chenwei Zhang, Haoming Jiang, Yifan Gao, Zheng Li, Xian Li, Chao Zhang, Bing Yin, William Wang, Xiaodan Zhu
Knowledge-Selective Pretraining for Attribute Value Extraction. EMNLP (Findings) (2023)
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 (2022)
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)
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 (2022)
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)
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 (2022)
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin
Condensing Graphs via One-Step Gradient Matching. KDD (2022)
Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR (2022)
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 (2022)
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)
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)
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying
Condensing Graphs via One-Step Gradient Matching. CoRR (2022)
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)
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 (2022)
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)
Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. CoRR (2021)
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 (2021)
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)
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)
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)
Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
Self-Training with Differentiable Teacher. CoRR (2021)
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)
Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
ARCH: Efficient Adversarial Regularized Training with Caching. CoRR (2021)
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 (2021)
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)
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)
Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao
Learning to Defend by Learning to Attack. AISTATS (2021)
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)
Haoming Jiang, Bo Dai, Mengjiao Yang, Wei Wei, Tuo Zhao
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. CoRR (2021)
Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao
Token-wise Curriculum Learning for Neural Machine Translation. CoRR (2021)
Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
Deep Reinforcement Learning with Smooth Policy. CoRR (2020)
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)
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 (2020)
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 (2020)
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)
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 (2020)
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 (2020)
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)
Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha
Transformer Hawkes Process. CoRR (2020)
Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha
Transformer Hawkes Process. ICML (2020)
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)
Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. ACL (2020)
Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
Deep Reinforcement Learning with Robust and Smooth Policy. ICML (2020)
Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao
Learning to Defense by Learning to Attack. DGS@ICLR (2019)
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)
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 (2019)
Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha
Meta Learning with Relational Information for Short Sequences. NeurIPS (2019)
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 (2019)
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)
Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
On Scalable and Efficient Computation of Large Scale Optimal Transport. DGS@ICLR (2019)
Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
On Scalable and Efficient Computation of Large Scale Optimal Transport. ICML (2019)
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 (2019)
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)
Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha
Meta Learning with Relational Information for Short Sequences. CoRR (2019)
Yifu Sun, Haoming Jiang
Contextual Text Denoising with Masked Language Models. CoRR (2019)
Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. NeurIPS (2019)
Yifu Sun, Haoming Jiang
Contextual Text Denoising with Masked Language Model. W-NUT@EMNLP (2019)
Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
On Scalable and Efficient Computation of Large Scale Optimal Transport. CoRR (2019)
Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. CoRR (2019)
Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. CoRR (2019)
Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
On Computation and Generalization of GANs with Spectrum Control. CoRR (2018)
Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao
Learning to Defense by Learning to Attack. CoRR (2018)