Aojun Zhou

Orcid: 0000-0002-4742-8624

According to our database1, Aojun Zhou authored at least 38 papers between 2017 and 2024.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2024

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
CoRR, 2024

MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs.
CoRR, 2024

Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models.
CoRR, 2024

NOAH: Learning Pairwise Object Category Attentions for Image Classification.
CoRR, 2024

Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation.
CoRR, 2024

NODI: Out-Of-Distribution Detection with Noise from Diffusion.
CoRR, 2024

2023
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation.
CoRR, 2023

MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.
CoRR, 2023

Efficient N: M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design.
CoRR, 2023

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification.
CoRR, 2023

JourneyDB: A Benchmark for Generative Image Understanding.
CoRR, 2023

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model.
CoRR, 2023

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.
CoRR, 2023

FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation.
CoRR, 2023

JourneyDB: A Benchmark for Generative Image Understanding.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SparseMAE: Sparse Training Meets Masked Autoencoders.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

CEST: Computation-Efficient N:M Sparse Training for Deep Neural Networks.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022
An Algorithm-Hardware Co-Optimized Framework for Accelerating N: M Sparse Transformers.
IEEE Trans. Very Large Scale Integr. Syst., 2022

Pyramid Fusion Transformer for Semantic Segmentation.
CoRR, 2022

Omni-Dimensional Dynamic Convolution.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Group R-CNN for Weakly Semi-supervised Object Detection with Points.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
DominoSearch: Find layer-wise fine-grained N: M sparse schemes from dense neural networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Group Fisher Pruning for Practical Network Compression.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning N: M Fine-grained Structured Sparse Neural Networks From Scratch.
Proceedings of the 9th International Conference on Learning Representations, 2021

Differentiable Dynamic Wirings for Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Incorporating Convolution Designs into Visual Transformers.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Dynamic Graph: Learning Instance-aware Connectivity for Neural Networks.
CoRR, 2020

2019
Towards Improving Generalization of Deep Networks via Consistent Normalization.
CoRR, 2019

Second Rethinking of Network Pruning in the Adversarial Setting.
CoRR, 2019

Adversarial Robustness vs. Model Compression, or Both?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Deeply-Supervised Knowledge Synergy.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Multisite Schizophrenia Classification Based on Brainnetome Atlas by Deep Learning.
Proceedings of the 5th IEEE International Conference on Cloud Computing and Intelligence Systems, 2018

Deep Neural Network Compression With Single and Multiple Level Quantization.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Incremental Network Quantization: Towards Lossless CNNs with Low-precision Weights.
Proceedings of the 5th International Conference on Learning Representations, 2017


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