mlsanityData to 14 Oct 2026

A Human-Computer Collaborative Tool for Training a Single Large Language Model Agent into a Network through Few Examples

arXiv 2404.15974 ↗First posted 24 Apr 2024cs.HCcited by 5

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

The capabilities of a single large language model (LLM) agent for solving a complex task are limited. Connecting multiple LLM agents to a network can effectively improve overall performance. However, building an LLM agent network (LAN) requires a substantial amount of time and effort. In this paper, we introduce EasyLAN, a human-computer collaborative tool that helps developers construct LANs. EasyLAN initially generates a LAN containing only one agent based on the description of the desired task. Subsequently, EasyLAN leverages a few training examples to update the LAN. For each example, EasyLAN models the gap between the output and the ground truth and identifies the causes of the errors. These errors are addressed through carefully designed strategies. Users can intervene in EasyLAN's workflow or directly modify the LAN. Eventually, the LAN evolves from a single agent to a network of LLM agents. The experimental results indicate that developers can rapidly construct LANs with good performance.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 51 of its 87 references that are in the map. First posted on arXiv 24 Apr 2024.

Builds on

51 of 87 references.

References · 51

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38 more
  1. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
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50 most cited of 51 All 51 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 1.

5 papers.

  1. 2025LLM-Based Human-Agent Collaboration and Interaction Systems: A Surveycited by 29
  2. 2025Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMscited by 19
  3. 2025Large language models for artificial general intelligence (AGI): A survey of foundational principles and approachescited by 18
  4. 2024Enhancing LLM Reasoning with Multi-Path Collaborative Reactive and Reflection agentscited by 15
  5. 2026Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studiescited by 1

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