IntentScore: Intent-Conditioned Action Evaluation for Computer-Use Agents
📰 ArXiv cs.AI
IntentScore is a plan-aware reward model that evaluates action quality for Computer-Use Agents to prevent irreversible errors
Action Steps
- Collect offline GUI interaction steps to train the IntentScore model
- Train IntentScore with complementary objectives to learn action evaluation
- Integrate IntentScore into Computer-Use Agents to score candidate actions
- Evaluate and refine IntentScore using feedback from GUI operations
Who Needs to Know This
AI engineers and researchers working on Computer-Use Agents can benefit from IntentScore to improve the reliability of their systems, and software engineers can apply this concept to develop more robust GUI automation tools
Key Insight
💡 IntentScore learns to score candidate actions to prevent irreversible errors in Computer-Use Agents
Share This
🤖 IntentScore: a plan-aware reward model to evaluate action quality for Computer-Use Agents 📊
DeepCamp AI