Visual Prompt Discovery via Semantic Exploration
Visual Prompt Discovery via Semantic Exploration explores An automated framework for discovering effective visual prompts to enhance LVLM perception through semantic exploration.. Commercial viability score: 7/10 in Visual Prompting.
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
MVP Investment
$9K - $13K
6-10 weeksEngineering
$8,000GPU Compute
$800SaaS Stack
$300Domain & Legal
$1006mo ROI
0.5-1x
3yr ROI
6-15x
GPU-heavy products have higher costs but premium pricing. Expect break-even by 12mo, then 40%+ margins at scale.
Talent Scout
Find Builders
Visual experts on LinkedIn & GitHub
Related Papers
- Builds On ThisVisual Persuasion: What Influences Decisions of Vision-Language Models?Viability: 6.0
- Builds On ThisDiffVP: Differential Visual Semantic Prompting for LLM-Based CT Report GenerationViability: 6.0
- Prior WorkSSVP: Synergistic Semantic-Visual Prompting for Industrial Zero-Shot Anomaly DetectionViability: 7.0
- Prior WorkEvolving Prompt Adaptation for Vision-Language ModelsViability: 7.0
- Prior WorkVirPro: Visual-referred Probabilistic Prompt Learning for Weakly-Supervised Monocular 3D Detection