mlsanityData to 14 Oct 2026

Multi-agent Application System in Office Collaboration Scenarios

arXiv 2503.19584 ↗First posted 25 Mar 2025cs.AI cs.CL cs.SEcited by 1

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Abstract (arXiv)

This paper introduces a multi-agent application system designed to enhance office collaboration efficiency and work quality. The system integrates artificial intelligence, machine learning, and natural language processing technologies, achieving functionalities such as task allocation, progress monitoring, and information sharing. The agents within the system are capable of providing personalized collaboration support based on team members' needs and incorporate data analysis tools to improve decision-making quality. The paper also proposes an intelligent agent architecture that separates Plan and Solver, and through techniques such as multi-turn query rewriting and business tool retrieval, it enhances the agent's multi-intent and multi-turn dialogue capabilities. Furthermore, the paper details the design of tools and multi-turn dialogue in the context of office collaboration scenarios, and validates the system's effectiveness through experiments and evaluations. Ultimately, the system has demonstrated outstanding performance in real business applications, particularly in query understanding, task planning, and tool calling. Looking forward, the system is expected to play a more significant role in addressing complex interaction issues within dynamic environments and large-scale multi-agent systems.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 31 of its 43 references that are in the map. First posted on arXiv 25 Mar 2025.

Builds on

31 of 43 references.

References · 31

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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Automated Mediator for Human Negotiation: Pre-Mediation via a Structured LLM Pipelinecited by 0

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  6. 2026Agentic Nesting: A New Methodology for Existing Enterprise Application Integration and Services
  7. 2026ProACT: Towards Breakdown-Aware Proactive Agent in Multi-User Collaboration
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