Qingru Zhang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Upper Confidence Bound

Reinforcement Learning

Top Venues

Publications

Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao
GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. CoRR (2024)
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR (2024)
Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao
Robust Reinforcement Learning from Corrupted Human Feedback. CoRR (2024)
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR (2023)
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) (2023)
Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. ICML (2023)
Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR (2023)
Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS (2023)
Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. ICML (2023)
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR (2023)
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR (2023)
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR (2023)
Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. CoRR (2023)
Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR (2022)
Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML (2022)
Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. NAACL-HLT (2022)
Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. CoRR (2022)
Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. CoRR (2022)
Qingru Zhang, David Wipf, Quan Gan, Le Song
A Biased Graph Neural Network Sampler with Near-Optimal Regret. NeurIPS (2021)
Qingru Zhang, David Wipf, Quan Gan, Le Song
A Biased Graph Neural Network Sampler with Near-Optimal Regret. CoRR (2021)
Zhiming Zhou, Qingru Zhang, Guansong Lu, Hongwei Wang, Weinan Zhang, Yong Yu
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods. ICLR (Poster) (2019)
Zhiming Zhou, Qingru Zhang, Guansong Lu, Hongwei Wang, Weinan Zhang, Yong Yu
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods. CoRR (2018)