Minghao Fu

Orcid: 0000-0002-4685-6600

Affiliations:
  • Nanjing University, School of Artificial Intelligence, National Key Laboratory for Novel Software Technology, China


According to our database1, Minghao Fu authored at least 16 papers between 2022 and 2025.

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

Timeline

Legend:

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Bibliography

2025
Images Speak Louder Than Scores: Failure Mode Escape for Enhancing Generative Quality.
CoRR, August, 2025

TeEFusion: Blending Text Embeddings to Distill Classifier-Free Guidance.
CoRR, July, 2025

QwT-v2: Practical, Effective and Efficient Post-Training Quantization.
CoRR, May, 2025

Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities.
CoRR, May, 2025

CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation.
CoRR, February, 2025

Minimal Interaction Seperated Tuning: A New Paradigm for Visual Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Quantization without Tears.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
Minimal Interaction Edge Tuning: A New Paradigm for Visual Adaptation.
CoRR, 2024

Low-rank Attention Side-Tuning for Parameter-Efficient Fine-Tuning.
CoRR, 2024

Unified Low-rank Compression Framework for Click-through Rate Prediction.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Rectify the Regression Bias in Long-Tailed Object Detection.
Proceedings of the Computer Vision - ECCV 2024, 2024

Instance-based Max-margin for Practical Few-shot Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

DTL: Disentangled Transfer Learning for Visual Recognition.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Instance-based Max-margin for Practical Few-shot Recognition.
CoRR, 2023

Multi-Label Self-Supervised Learning with Scene Images.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Worst Case Matters for Few-Shot Recognition.
Proceedings of the Computer Vision - ECCV 2022, 2022


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