Learning to Defense by Learning to Attack. - Zhehui Chen; Haoming Jiang; Bo Dai 001; Tuo Zhao (CoRR, 2018)

On Computation and Generalization of GANs with Spectrum Control. - Haoming Jiang; Zhehui Chen; Minshuo Chen; Feng Liu; Dingding Wang 001; Tuo Zhao (CoRR, 2018)

Contextual Text Denoising with Masked Language Model. - Yifu Sun; Haoming Jiang (W-NUT@EMNLP, 2019)

Learning to Defense by Learning to Attack. - Zhehui Chen; Haoming Jiang; Yuyang Shi 001; Bo Dai 001; Tuo Zhao (DGS@ICLR, 2019)

On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. - Haoming Jiang; Zhehui Chen; Minshuo Chen; Feng Liu; Dingding Wang 001; Tuo Zhao (ICLR (Poster), 2019)

On Scalable and Efficient Computation of Large Scale Optimal Transport. - Yujia Xie; Minshuo Chen; Haoming Jiang; Tuo Zhao; Hongyuan Zha (ICML, 2019)

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. - Minshuo Chen; Haoming Jiang; Wenjing Liao; Tuo Zhao (NeurIPS, 2019)

Meta Learning with Relational Information for Short Sequences. - Yujia Xie; Haoming Jiang; Feng Liu; Tuo Zhao; Hongyuan Zha (NeurIPS, 2019)

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. - Xingguo Li; Haoming Jiang; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (UAI, 2019)

Contextual Text Denoising with Masked Language Models. - Yifu Sun; Haoming Jiang (CoRR, 2019)

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. - Jason Ge; Xingguo Li; Haoming Jiang; Han Liu 001; Tong Zhang 001; Mengdi Wang; Tuo Zhao (J. Mach. Learn. Res., 2019)

Designing deployable 3D scissor structures with ball-and-socket joints. - Xuejin Chen; Haoming Jiang; Tingting Xuan; Lihan Huang; Ligang Liu 001 (Comput. Animat. Virtual Worlds, 2019)

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. - Haoming Jiang; Pengcheng He; Weizhu Chen; Xiaodong Liu 003; Jianfeng Gao 001; Tuo Zhao (ACL, 2020)

Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. - Haoming Jiang; Chen Liang 006; Chong Wang; Tuo Zhao (ACL, 2020)

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. - Lingkai Kong; Haoming Jiang; Yuchen Zhuang; Jie Lyu 005; Tuo Zhao; Chao Zhang 014 (EMNLP (1), 2020)

On the Variance of the Adaptive Learning Rate and Beyond. - Liyuan Liu; Haoming Jiang; Pengcheng He; Weizhu Chen; Xiaodong Liu 003; Jianfeng Gao 001; Jiawei Han 001 (ICLR, 2020)

Deep Reinforcement Learning with Robust and Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (ICML, 2020)

Transformer Hawkes Process. - Simiao Zuo; Haoming Jiang; Zichong Li; Tuo Zhao; Hongyuan Zha (ICML, 2020)

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. - Chen Liang 006; Yue Yu 001; Haoming Jiang; Siawpeng Er; Ruijia Wang; Tuo Zhao; Chao Zhang 014 (KDD, 2020)

Deep Reinforcement Learning with Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (CoRR, 2020)

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. - Haoming Jiang; Danqing Zhang; Tianyu Cao 001; Bing Yin; Tuo Zhao (ACL/IJCNLP (1), 2021)

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. - Chen Liang 006; Simiao Zuo; Minshuo Chen; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Tuo Zhao; Weizhu Chen (ACL/IJCNLP (1), 2021)

Learning to Defend by Learning to Attack. - Haoming Jiang; Zhehui Chen; Yuyang Shi 001; Bo Dai 001; Tuo Zhao (AISTATS, 2021)

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. - Haoming Jiang; Bo Dai 001; Mengjiao Yang 001; Tuo Zhao; Wei Wei 019 (EMNLP (1), 2021)

Token-wise Curriculum Learning for Neural Machine Translation. - Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001; Tuo Zhao (EMNLP (Findings), 2021)

ARCH: Efficient Adversarial Regularized Training with Caching. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (Findings), 2021)

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (1), 2021)

Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. - Yue Yu 001; Simiao Zuo; Haoming Jiang; Wendi Ren; Tuo Zhao; Chao Zhang 014 (NAACL-HLT, 2021)

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (CoRR, 2021)

Reducing Human Labor Cost in Deep Learning for Natural Language Processing. - Haoming Jiang (2021)

Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. - Zijie Huang 002; Zheng Li 018; Haoming Jiang; Tianyu Cao 001; Hanqing Lu; Bing Yin; Karthik Subbian; Yizhou Sun; Wei Wang 010 (ACL (1), 2022)

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. - Chen Liang 006; Haoming Jiang; Simiao Zuo; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (ICLR, 2022)

Condensing Graphs via One-Step Gradient Matching. - Wei Jin 009; Xianfeng Tang; Haoming Jiang; Zheng Li 018; Danqing Zhang; Jiliang Tang; Bing Yin (KDD, 2022)

AutoGDA: Automated Graph Data Augmentation for Node Classification. - Tong Zhao 003; Xianfeng Tang; Danqing Zhang; Haoming Jiang; Nikhil Rao 001; Yiwei Song; Pallav Agrawal; Karthik Subbian; Bing Yin; Meng Jiang 001 (LoG, 2022)

SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models. - Jingfeng Yang 001; Haoming Jiang; Qingyu Yin; Danqing Zhang; Bing Yin; Diyi Yang (NAACL-HLT (Findings), 2022)

Self-Training with Differentiable Teacher. - Simiao Zuo; Yue Yu 001; Chen Liang 006; Haoming Jiang; Siawpeng Er; Chao Zhang 014; Tuo Zhao; Hongyuan Zha (NAACL-HLT (Findings), 2022)

Query Attribute Recommendation at Amazon Search. - Chen Luo 003; William Headden; Neela Avudaiappan; Haoming Jiang; Tianyu Cao 001; Qingyu Yin; Yifan Gao 001; Zheng Li 018; Rahul Goutam; Haiyang Zhang; Bing Yin (RecSys, 2022)

Condensing Graphs via One-Step Gradient Matching. - Wei Jin 009; Xianfeng Tang; Haoming Jiang; Zheng Li 018; Danqing Zhang; Jiliang Tang; Bin Ying (CoRR, 2022)

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. - Simiao Zuo; Haoming Jiang; Qingyu Yin; Xianfeng Tang; Bing Yin; Tuo Zhao (CoRR, 2022)

Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding. - Haoming Jiang; Tianyu Cao 001; Zheng Li 018; Chen Luo 003; Xianfeng Tang; Qingyu Yin; Danqing Zhang; Rahul Goutam; Bing Yin (CoRR, 2022)

Graph Reasoning for Question Answering with Triplet Retrieval. - Shiyang Li; Yifan Gao 001; Haoming Jiang; Qingyu Yin; Zheng Li 018; Xifeng Yan; Chao Zhang 014; Bing Yin (ACL (Findings), 2023)

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. - Simiao Zuo; Qingyu Yin; Haoming Jiang; Shaohui Xi; Bing Yin; Chao Zhang 014; Tuo Zhao (ACL (industry), 2023)

SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce. - Karan Samel; Houyu Zhang; Jun Ma 029; Haoming Jiang; Qing Ping; Sheng Wang 012; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (IEEE Big Data, 2023)

Knowledge-Selective Pretraining for Attribute Value Extraction. - Hui Liu 033; Qingyu Yin; Zhengyang Wang; Chenwei Zhang; Haoming Jiang; Yifan Gao 001; Zheng Li 018; Xian Li; Chao Zhang 014; Bing Yin; William Wang 001; Xiaodan Zhu 001 (EMNLP (Findings), 2023)

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. - Chen Liang 006; Haoming Jiang; Zheng Li 018; Xianfeng Tang; Bing Yin; Tuo Zhao (ICLR, 2023)

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. - Zichong Li; Yanbo Xu; Simiao Zuo; Haoming Jiang; Chao Zhang; Tuo Zhao; Hongyuan Zha (ICML, 2023)

LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. - Haoyu Wang 004; Ruirui Li 002; Haoming Jiang; Zhengyang Wang; Xianfeng Tang; Bin Bi; Monica Xiao Cheng; Bing Yin; Yaqing Wang 001; Tuo Zhao; Jing Gao 004 (KDD, 2023)

Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. - Wei Jin 009; Haitao Mao; Zheng Li 018; Haoming Jiang; Chen Luo 003; Hongzhi Wen; Haoyu Han 001; Hanqing Lu; Zhengyang Wang; Ruirui Li 002; Zhen Li; Monica Xiao Cheng; et al. (NeurIPS, 2023)

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. - Chen Liang 006; Haoming Jiang; Zheng Li 018; Xianfeng Tang; Bin Yin; Tuo Zhao (CoRR, 2023)

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. - Jingfeng Yang 001; Hongye Jin; Ruixiang Tang; Xiaotian Han; Qizhang Feng; Haoming Jiang; Bing Yin; Xia Hu 001 (CoRR, 2023)

CCGen: Explainable Complementary Concept Generation in E-Commerce. - Jie Huang 009; Yifan Gao 001; Zheng Li 018; Jingfeng Yang 001; Yangqiu Song; Chao Zhang 014; Zining Zhu 001; Haoming Jiang; Kevin Chen-Chuan Chang; Bing Yin (CoRR, 2023)

Situated Natural Language Explanations. - Zining Zhu 001; Haoming Jiang; Jingfeng Yang 001; Sreyashi Nag; Chao Zhang 014; Jie Huang 009; Yifan Gao 001; Frank Rudzicz; Bing Yin (CoRR, 2023)

Data Diversity Matters for Robust Instruction Tuning. - Alexander Bukharin; Shiyang Li; Zhengyang Wang; Jingfeng Yang 001; Bing Yin; Xian Li; Chao Zhang 014; Tuo Zhao; Haoming Jiang (EMNLP (Findings), 2024)

Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark. - Fenglin Liu; Zheng Li 018; Hongjian Zhou; Qingyu Yin; Jingfeng Yang 001; Xianfeng Tang; Chen Luo 003; Ming Zeng 001; Haoming Jiang; Yifan Gao 001; Priyanka Nigam; Sreyashi Nag; et al. (EMNLP, 2024)

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. - Haoyu Wang 004; Ruirui Li 002; Haoming Jiang; Jinjin Tian; Zhengyang Wang; Chen Luo 003; Xianfeng Tang; Monica Xiao Cheng; Tuo Zhao; Jing Gao 004 (EMNLP, 2024)

MEMORYLLM: Towards Self-Updatable Large Language Models. - Yu Wang 170; Yifan Gao 001; Xiusi Chen; Haoming Jiang; Shiyang Li; Jingfeng Yang 001; Qingyu Yin; Zheng Li 018; Xian Li; Bing Yin; Jingbo Shang; Julian J. McAuley (ICML, 2024)

Robust Reinforcement Learning from Corrupted Human Feedback. - Alexander Bukharin; Ilgee Hong; Haoming Jiang; Zichong Li; Qingru Zhang; Zixuan Zhang; Tuo Zhao (NeurIPS, 2024)

Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. - Ilgee Hong; Zichong Li; Alexander Bukharin; Yixiao Li; Haoming Jiang; Tianbao Yang; Tuo Zhao (NeurIPS, 2024)

Robust Reinforcement Learning from Corrupted Human Feedback. - Alexander Bukharin; Ilgee Hong; Haoming Jiang; Qingru Zhang; Zixuan Zhang; Tuo Zhao (CoRR, 2024)

Relational Database Augmented Large Language Model. - Zongyue Qin; Chen Luo 003; Zhengyang Wang; Haoming Jiang; Yizhou Sun (CoRR, 2024)

Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs. - Kewei Cheng; Jingfeng Yang 001; Haoming Jiang; Zhengyang Wang; Binxuan Huang; Ruirui Li 002; Shiyang Li; Zheng Li 018; Yifan Gao 001; Xian Li; Bing Yin; Yizhou Sun (CoRR, 2024)

RNR: Teaching Large Language Models to Follow Roles and Rules. - Kuan Wang; Alexander Bukharin; Haoming Jiang; Qingyu Yin; Zhengyang Wang; Tuo Zhao; Jingbo Shang; Chao Zhang 014; Bing Yin; Xian Li; Jianshu Chen; Shiyang Li (CoRR, 2024)

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. - Jingfeng Yang 001; Hongye Jin; Ruixiang Tang; Xiaotian Han; Qizhang Feng; Haoming Jiang; Shaochen Zhong; Bing Yin; Xia Ben Hu (ACM Trans. Knowl. Discov. Data, 2024)

IHEval: Evaluating Language Models on Following the Instruction Hierarchy. - Zhihan Zhang 001; Shiyang Li; Zixuan Zhang; Xin Liu 039; Haoming Jiang; Xianfeng Tang; Yifan Gao 001; Zheng Li 018; Haodong Wang; Zhaoxuan Tan; Yichuan Li 001; Qingyu Yin; et al. (NAACL (Long Papers), 2025)

Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training. - Yuchen Zhuang; Jingfeng Yang 001; Haoming Jiang; Xin Liu 039; Kewei Cheng; Sanket Lokegaonkar; Yifan Gao 001; Qing Ping; Tianyi Liu; Binxuan Huang; Zheng Li 018; Zhengyang Wang; et al. (NAACL (Long Papers), 2025)

Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models. - Ilgee Hong; Changlong Yu; Liang Qiu; Weixiang Yan; Zhenghao Xu; Haoming Jiang; Qingru Zhang; Qin Lu; Xin Liu; Chao Zhang; Tuo Zhao (CoRR, 2025)

RRO: LLM Agent Optimization Through Rising Reward Trajectories. - Zilong Wang 002; Jingfeng Yang 001; Sreyashi Nag; Samarth Varshney; Xianfeng Tang; Haoming Jiang; Jingbo Shang; Sheikh Muhammad Sarwar (CoRR, 2025)