mlsanityData to 14 Oct 2026

ScheduleMe: Multi-Agent Calendar Assistant

arXiv 2509.25693 ↗First posted 30 Sep 2025cs.AIcited by 1

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

Abstract (arXiv)

Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper presents a ScheduleMe, a multi-agent calendar assistant for users to manage google calendar events in natural language. The system uses a graph-structured coordination mechanism where a central supervisory agent supervises specialized task agents, allowing modularity, conflicts resolution, and context-aware interactions to resolve ambiguities and evaluate user commands. This approach sets an example of how structured reasoning and agent cooperation might convince operators to increase the usability and flexibility of personal calendar assistant tools.

Key facts. Cited by 1 paper 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 16 of its 32 references that are in the map. First posted on arXiv 30 Sep 2025.

Builds on

16 of 32 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Exploration of LLM Multi-Agent Application Implementation Based on LangGraph+CrewAI27 Nov
  2. 2023A Survey on Large Language Model based Autonomous Agents22 Aug

Other references · 14

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  4. 2023Auto-GPT for Online Decision Making: Benchmarks and Additional Opinionscited by 255
  5. 2022Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP Worldcited by 55
  6. 2023SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledgecited by 49
  7. 2017Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loopcited by 26
  8. 2024SMARTCAL: An Approach to Self-Aware Tool-Use Evaluation and Calibrationcited by 13
  9. 2023Evaluating Task-oriented Dialogue Systems: A Systematic Review of Measures, Constructs and their Operationalisationscited by 9
  10. 2025Zero-shot OCR Accuracy of Low-Resourced Languages: A Comparative Analysis on Sinhala and Tamilcited by 9
  11. 2017Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similaritycited by 8
  12. 2025Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systemscited by 8
2 more
  1. 2025Evolution of Cooperation in LLM-Agent Societies: A Preliminary Study Using Different Punishment Strategiescited by 6
  2. 2023ScriptWorld: Text Based Environment For Learning Procedural Knowledgecited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

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  3. 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
  4. 2026ProEvent: An Event-centric Benchmark for Proactive Agents
  5. 2023Towards A Natural Language Interface for Flexible Multi-Agent Task Assignment
  6. 2024Controllable and Reliable Knowledge-Intensive Task-Oriented Conversational Agents with Declarative Genie Worksheets
  7. 2026PEARL: Self-Evolving Assistant for Time Management with Reinforcement Learning
  8. 2025Agent-Initiated Interaction in Phone UI Automation