Places365

anchor

Note

named in the citing paper without a reference entry, so there is no citable anchor

Findings

• IC-028SPADE, an abstaining classifier built on top of ResNet, ViT, and VGG models, detects out-of-distribution and adversarial samples with provable guarantees. [eval]
• IC-643Conditioning CLIP on correct contextual attributes in the text prompt improves zero-shot classification accuracy across 13 image transformations [eval]
• IC-737CLIP ViT-B/16 binarized dot products yield 0.50–0.58 accuracy on binary concept presence queries across five image classification datasets [eval]
• IC-738BLIP-2 ViT-G FlanT5XL achieves 0.70–0.87 zero-shot accuracy on binary concept presence queries, competitive on most datasets but weaker on fine-grained CUB-200 [eval]
• IC-739GPT-3.5-turbo-0613 combined with CLIP produces more faithful concept-salience pseudo-labels than LLaMA-2-13B-Chat, InstructBLIP, or LLaVA-1.5B on most of five datasets [eval]
• IC-990ResNet-50 and DenseNet-101 exhibit a higher mean-to-variance ratio in penultimate pre-ReLU activations for in-distribution samples than for out-of-distribution samples, and the activation-based scaling factor is well-separated between ID and OOD [eval]