Qingru Zhang

According to our database1, Qingru Zhang authored at least 12 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM.
CoRR, 2024

2023
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.
CoRR, 2023

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation.
CoRR, 2023

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Less is More: Task-aware Layer-wise Distillation for Language Model Compression.
Proceedings of the International Conference on Machine Learning, 2023

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation.
Proceedings of the International Conference on Machine Learning, 2023

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance.
Proceedings of the International Conference on Machine Learning, 2022

2021
A Biased Graph Neural Network Sampler with Near-Optimal Regret.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods.
Proceedings of the 7th International Conference on Learning Representations, 2019


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