Papers with agent generation

2 papers
AgentInit: Initializing LLM-based Multi-Agent Systems via Diversity and Expertise Orchestration for Effective and Efficient Collaboration (2025.findings-emnlp)

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Challenge: Existing MAS initialization methods do not fully account for the collaborative needs of the generated agents in subsequent stages.
Approach: They propose to use a Natural Language to Format mechanism to optimize the structure of agent teams and incorporate a natural language to format mechanism to ensure consistency and standardization.
Outcome: The proposed method outperforms state-of-the-art initialization methods and pre-defined strategies across various frameworks and tasks while reducing token consumption.
ReCreate: Reasoning and Creating Domain Agents Driven by Experience (2026.acl-long)

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Challenge: Large Language Model (LLM) agents are reshaping the industrial landscape, but tasks differ widely, making them labor-intensive to build.
Approach: They propose an experience-driven framework for the automatic creation of domain agents . they leverage agent interaction histories to provide rich concrete signals on success or failure .
Outcome: The proposed framework outperforms human-designed agents and existing methods in experiments across diverse domains.

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