FOCI adds a post-hoc readout to frozen WSI-MIL models to find compact output-consistent tile subsets and measures selection headroom with SHI, showing transformer-based models allow smaller rationales than attention-pooling baselines.
Grad-cam: Visual explanations from deep networks via gradient-based localization
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TAP uses two-stage pretraining on unlabeled data to learn physical competence before language grounding, matching 1M-expert models with far less labeled data and showing robustness on real robots.
SEF introduces GAN upsampling for diverse artifacts and expert fusion to reduce domain interference, yielding stronger generalization on 13 benchmarks for AI-generated image detection.
Pretrained instruction-based image editing models exhibit early foreground-background separability that enables a training-free framework for zero-shot referring image segmentation using a single denoising step.
Uncertainty-aware extensions to Variational Information Pursuit (EUAV-IP and IUAV-IP) improve reliability and conciseness of concept-based predictions on five medical imaging datasets.
Benchmark study of ten GNN explainers on eight architectures and six datasets that isolates usable components and issues practical recommendations.
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