Webquery: a simple web-enabled system for database management. - Ping Wang; Qingru Zhang (J. Comput. Sci. Coll., 2002)

AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods. - Zhiming Zhou 001; Qingru Zhang; Guansong Lu; Hongwei Wang 004; Weinan Zhang 001; Yong Yu 001 (ICLR (Poster), 2019)

A Biased Graph Neural Network Sampler with Near-Optimal Regret. - Qingru Zhang; David Wipf; Quan Gan; Le Song (NeurIPS, 2021)

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. - Qingru Zhang; Simiao Zuo; Chen Liang 006; Alexander Bukharin; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2022)

MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. - Simiao Zuo; Qingru Zhang; Chen Liang 006; Pengcheng He; Tuo Zhao; Weizhu Chen (NAACL-HLT, 2022)

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 (EMNLP (Findings), 2023)

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. - Qingru Zhang; Minshuo Chen; Alexander Bukharin; Pengcheng He; Yu Cheng 001; Weizhu Chen; Tuo Zhao (ICLR, 2023)

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. - Yixiao Li; Yifan Yu 008; Qingru Zhang; Chen Liang 006; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

Less is More: Task-aware Layer-wise Distillation for Language Model Compression. - Chen Liang 006; Simiao Zuo; Qingru Zhang; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. - Alexander Bukharin; Yan Li; Yue Yu 001; Qingru Zhang; Zhehui Chen; Simiao Zuo; Chao Zhang 014; Songan Zhang; Tuo Zhao (NeurIPS, 2023)

GEAR: An Efficient Error Reduction Framework for KV Cache Compression in LLM Inference. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (ENLSP, 2024)

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. - Qingru Zhang; Chandan Singh; Liyuan Liu; Xiaodong Liu 003; Bin Yu 001; Jianfeng Gao 001; Tuo Zhao (ICLR, 2024)

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

GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. - Hao Kang; Qingru Zhang; Souvik Kundu 009; Geonhwa Jeong; Zaoxing Liu; Tushar Krishna; Tuo Zhao (CoRR, 2024)

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

Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering. - Qingru Zhang; Xiaodong Yu 003; Chandan Singh; Xiaodong Liu 003; Liyuan Liu; Jianfeng Gao 001; Tuo Zhao; Dan Roth 001; Hao Cheng 002 (CoRR, 2024)

Multiscale Spatio-Temporal Fusion Network for video dehazing. - Qingru Zhang; Guorong Chen; Yixuan Zhang; Jinmei Zhang; Shaofeng Liu; Jian Wang (Comput. Vis. Image Underst., 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)

Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs. - Hao Kang; Qingru Zhang; Han Cai; Weiyuan Xu; Tushar Krishna; Yilun Du; Tsachy Weissman (CoRR, 2025)