| 2026 | ACL | OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment. | Tianci Liu, Ran Xu, Tony Yu, Ilgee Hong, Carl Yang, Tuo Zhao, Haoyu Wang |
| 2025 | ACL | RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. | Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang |
| 2025 | EMNLP | DORM: Preference Data Weights Optimization for Reward Modeling in LLM Alignment. | Rongzhi Zhang, Chenwei Zhang, Xinyang Zhang, Liang Qiu, Haoming Jiang, Yuchen Zhuang, Qingru Zhang, Hyokun Yun, Xian Li, Bing Yin, Tuo Zhao, Chao Zhang |
| 2025 | ICASSP | MS-RainMamba: Learning Multi-Scale State Space Models for Single Image Deraining. | Haibo Li, Zhanshuo Liu, Tuo Zhao, Tingting Zhao, Yarui Chen, Ning Xie |
| 2025 | ICML | Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data. | Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang |
| 2025 | ICML | Deep Reinforcement Learning from Hierarchical Preference Design. | Alexander Bukharin, Yixiao Li, Pengcheng He, Tuo Zhao |
| 2024 | EMNLP | RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. | Haoyu Wang, Tianci Liu, Ruirui Li, Monica Xiao Cheng, Tuo Zhao, Jing Gao |
| 2024 | EMNLP | Data Diversity Matters for Robust Instruction Tuning. | Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang |
| 2024 | EMNLP | BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. | Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao Cheng, Tuo Zhao, Jing Gao |
| 2024 | ICLR | LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. | Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao |
| 2024 | ICLR | Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. | Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao |
| 2024 | ICML | Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process. | Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha |
| 2024 | ICML | To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. | Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang |
| 2024 | IECON | A Cloud-Edge Intelligent Collaborative Framework and Its Applications in AIGC and Digital Twins. | Haiteng Wang, Lu Jiao, Tuo Zhao, Lei Ren |
| 2023 | ACL | 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, Tuo Zhao |
| 2023 | AISTATS | Reinforcement Learning for Adaptive Mesh Refinement. | Jiachen Yang, Tarik Dzanic, Brenden K. Petersen, Jun Kudo, Ketan Mittal, Vladimir Z. Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio V. Kolev, Robert W. Anderson, Daniel M. Faissol |
| 2023 | EMNLP | HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference. | Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao |
| 2023 | EMNLP | Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. | Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao |
| 2023 | ICASSP | Joint Estimation of DOA and Distance in Noisy Reverberant Conditions. | Suliang Bu, Tuo Zhao, Yunxin Zhao |
| 2023 | ICLR | Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. | Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao |
| 2023 | ICLR | HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. | Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao |
| 2023 | ICLR | Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. | Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao |
| 2023 | ICML | Machine Learning Force Fields with Data Cost Aware Training. | Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao |
| 2023 | ICML | Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. | Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang |
| 2023 | ICML | Less is More: Task-aware Layer-wise Distillation for Language Model Compression. | Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao |
| 2023 | ICML | 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 |
| 2023 | ICML | LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. | Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao |
| 2023 | ICML | Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. | Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao |
| 2023 | KDD | LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. | Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao |
| 2022 | ACL | CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. | Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao |
| 2022 | AISTATS | Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. | Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao |
| 2022 | ICLR | No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. | Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao |
| 2022 | ICLR | Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. | Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan |
| 2022 | ICLR | Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. | Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao |
| 2022 | ICLR | Taming Sparsely Activated Transformer with Stochastic Experts. | Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao |
| 2022 | ICML | Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. | Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao |
| 2022 | ICML | PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. | Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao |
| 2022 | Interspeech | Steering vector correction in MVDR beamformer for speech enhancement. | Suliang Bu, Yunxin Zhao, Tuo Zhao |
| 2022 | NAACL | CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. | Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang |
| 2022 | NAACL | Self-Training with Differentiable Teacher. | Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha |
| 2022 | NAACL | MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. | Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen |
| 2021 | ACL | Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. | Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao |
| 2021 | ACL | Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. | Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen |
| 2021 | AISTATS | Learning to Defend by Learning to Attack. | Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao |
| 2021 | AISTATS | Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. | Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao |
| 2021 | CIKM | QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction. | Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang |
| 2021 | EMNLP | Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. | Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei |
| 2021 | EMNLP | Token-wise Curriculum Learning for Neural Machine Translation. | Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao |
| 2021 | EMNLP | ARCH: Efficient Adversarial Regularized Training with Caching. | Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao |
| 2021 | EMNLP | Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. | Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao |
| 2021 | ICLR | A Hypergradient Approach to Robust Regression without Correspondence. | Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha |
| 2021 | ICML | How Important is the Train-Validation Split in Meta-Learning? | Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong |
| 2021 | ICML | Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. | Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao |
| 2021 | NAACL | Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. | Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang |
| 2020 | ACL | SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. | Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao |
| 2020 | ACL | Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. | Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao |
| 2020 | AISTATS | On Generalization Bounds of a Family of Recurrent Neural Networks. | Minshuo Chen, Xingguo Li, Tuo Zhao |
| 2020 | EMNLP | Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. | Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang |
| 2020 | ICLR | On Computation and Generalization of Generative Adversarial Imitation Learning. | Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao |
| 2020 | ICLR | Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. | Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao |
| 2020 | ICML | Deep Reinforcement Learning with Robust and Smooth Policy. | Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao |
| 2020 | ICML | Transformer Hawkes Process. | Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha |
| 2020 | KDD | BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. | Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang |
| 2019 | AISTATS | On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. | Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao |
| 2019 | ICLR | Learning to Defense by Learning to Attack. | Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao |
| 2019 | ICLR | On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. | Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao |
| 2019 | ICLR | On Scalable and Efficient Computation of Large Scale Optimal Transport. | Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha |
| 2019 | ICML | On Scalable and Efficient Computation of Large Scale Optimal Transport. | Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha |
| 2019 | ICML | Toward Understanding the Importance of Noise in Training Neural Networks. | Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao |
| 2019 | UAI | 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, Mingyi Hong, Tuo Zhao |
| 2019 | UAI | Online Factorization and Partition of Complex Networks by Random Walk. | Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang |
| 2018 | ITA | Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. | Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao |
| 2017 | ICML | Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability. | Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao |
| 2017 | Interspeech | The Opensesame NIST 2016 Speaker Recognition Evaluation System. | Gang Liu, Qi Qian, Zhibin Wang, Qingen Zhao, Tianzhou Wang, Hao Li, Jian Xue, Shenghuo Zhu, Rong Jin, Tuo Zhao |
| 2016 | AISTATS | An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. | Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong |
| 2016 | ICML | Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. | Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt |
| 2016 | IGARSS | Subpixel mapping of hyperspectral images based on collaborative representation. | Xiaoqin Xue, Yifan Zhang, Tuo Zhao, Mingyi He |
| 2016 | IGARSS | Hyperspectral and multispectral image fusion using collaborative representation with local adaptive dictionary pair. | Tuo Zhao, Yifan Zhang, Xiaoqin Xue, Mingyi He |
| 2015 | Interspeech | Time-frequency kernel-based CNN for speech recognition. | Tuo Zhao, Yunxin Zhao, Xin Chen |
| 2006 | ACIVS | Curve Mapping Based Illumination Adjustment for Face Detection. | Xiaoyue Jiang, Tuo Zhao, Rongchun Zhao |
| 2006 | ICPR | Feature selection for linear support vector machines. | Zhizheng Liang, Tuo Zhao |
| 2005 | CAIP | Re-lighting and Compensation for Face Images. | Xiaoyue Jiang, Tuo Zhao, Rong Xiao, Rongchun Zhao |