Evo2Team: When Do Evolved Skills Transfer? From Selection to Deployment
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Sources
- FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
- AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs
- SkillCommit: Evolving Agent Skills through Behaviorally Validated Scope Expansion
- SkillGen: Verified Inference-Time Agent Skill Synthesis
- RouteLLM: Learning to Route LLMs with Preference Data
- Reflexion: Language Agents with Verbal Reinforcement Learning
- Voyager: An Open-Ended Embodied Agent with Large Language Models
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
- SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
- AFlow: Automating Agentic Workflow Generation
- Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
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