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Found 4 papers, 2 papers with code
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Diffusion Denoising Probability Models (DDPM) and Vision Transformer (ViT) have demonstrated significant progress in generative tasks and discriminative tasks, respectively, and thus far these models have largely been developed in their own domains.
Robust Information Retrieval for False Claims with Distracting Entities In Fact Extraction and Verification
A BERT-based retrieval model made more mistakes in retrieving refuting evidence for false claims than supporting evidence for true claims.
GANMEX: Class-Targeted One-vs-One Attributions using GAN-based Model Explainability
Our approach effectively selects the baseline as the closest realistic sample belong to the target class, which allows attribution methods to provide true one-vs-one explanations.
GANMEX: One-vs-One Attributions Guided by GAN-based Counterfactual Explanation Baselines
Attribution methods have been shown as promising approaches for identifying key features that led to learned model predictions.
