Alibaba’s AgentEvolver increases tooling model performance by approximately 30% using automatically generated synthetic tasks
Researchers at Alibaba’s Tongyi Lab have developed a new framework for self-evolving agents that create their own training data by exploring their application environments. The frame, AgentEvolveruses the knowledge and reasoning capabilities of large language models for autonomous learning, addressing the high costs and manual effort typically required to collect task-specific data sets. Experiments show…
