EMHO: EMbodied Agent Harness Optimization via Experience Traces
cs.AI
Submitted: 2026-10-06
Updated: 2026-10-06
Terminology
Sources
- EmbodiSkill: Skill-Aware Reflection for Self-Evolving Embodied Agents
- Meta-Harness: End-to-End Optimization of Model Harnesses
- Depth Anything 3: Recovering the Visual Space from Any Views
- Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses
- OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics
- ASPIRE: Agentic /Skills Discovery for Robotics
- VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents
- Self-Harness: Harnesses That Improve Themselves
- Enabling Extensible Embodied Capabilities with Tools
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems