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Reliable prediction by classifiers is crucial for their deployment in high security and dynamically changing situations.
The relationship between precision-recall and roc curves
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Imagenet: A large-scale hierarchical image database
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Training independent subnetworks for robust prediction
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Anomaly detection in video via self-supervised and multi-task learning
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Learning transferable visual models from natural language supervision
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Videoclip: Contrastive pre-training for zero-shot video-text understanding
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Large-scale zero-shot image classification from rich and diverse textual descriptions
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Align before fuse: Vision and language representation learning with momentum distillation
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Vilt: Vision-and-language transformer without convolution or region supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim · 2021
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Tip-adapter: Training-free clip-adapter for better vision-language modeling
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Delving into out-of-distribution detection with vision-language representations
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Unified classification and rejection: A one-versus-all framework
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Openmix: Exploring outlier samples for misclassification detection
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Revisiting confidence estimation: Towards reliable failure prediction
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Clip-adapter: Better vision-language models with feature adapters
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Natural adversarial examples
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The many faces of robustness: A critical analysis of out-of-distribution generalization
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Rethinking confidence calibration for failure prediction
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Out-of-distribution detection with deep nearest neighbors
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Visual prompt tuning
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Training with scaled logits to alleviate class-level over-fitting in few-shot learning
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Locoop: Few-shot out-of-distribution detection via prompt learning
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Average of pruning: Improving performance and stability of out-of-distribution detection
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Open-world machine learning: A review and new outlooks
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Rcl: Reliable continual learning for unified failure detection
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
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Desire: Dynamic knowledge consolidation for rehearsal-free continual learning
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Towards trustworthy dataset distillation
Shijie Ma, Fei Zhu, Zhen Cheng, and Xu-Yao Zhang · 2024
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Modalprompt: Dual-modality guided prompt for continual learning of large multimodal models
Fanhu Zeng, Fei Zhu, Haiyang Guo, Xu-Yao Zhang, and Cheng-Lin Liu · 2024
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Breaking the limits of reliable prediction via generated data
Zhen Cheng, Fei Zhu, Xu-Yao Zhang, and Cheng-Lin Liu · 2024
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Federated continual instruction tuning
Haiyang Guo, Fanhu Zeng, Fei Zhu, Wenzhuo Liu, Da-Han Wang, Jian Xu, Xu-Yao Zhang, and Cheng-Lin Liu · 2025
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Local-prompt: Extensible local prompts for few-shot out-of-distribution detection
Fanhu Zeng, Zhen Cheng, Fei Zhu, Hongxin Wei, and Xu-Yao Zhang · 2025
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Haiyang Guo, Fanhu Zeng, Ziwei Xiang, Fei Zhu, Da-Han Wang, Xu-Yao Zhang, and Cheng-Lin Liu · 2025
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