What Helps -- and What Hurts: Bidirectional Explanations for Vision Transformers
What Helps -- and What Hurts: Bidirectional Explanations for Vision Transformers explores Develop a tool for generating bidirectional explanations for Vision Transformers using BiCAM, enhancing interpretability and adversarial detection.. Commercial viability score: 3/10 in Transformer Interpretability.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Prior WorkDo All Vision Transformers Need Registers? A Cross-Architectural ReassessmentViability: 3.0
- Higher ViabilityFusion-CAM: Integrating Gradient and Region-Based Class Activation Maps for Robust Visual ExplanationsViability: 7.0
- Higher ViabilityCAViT -- Channel-Aware Vision Transformer for Dynamic Feature FusionViability: 7.0
- Higher ViabilityViT-Explainer: An Interactive Walkthrough of the Vision Transformer PipelineViability: 5.0
- Higher ViabilityHAViT: Historical Attention Vision Transformer