mlsanityData to 14 Oct 2026

EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation

arXiv 2505.06904 ↗First posted 11 May 2025cs.CL cs.CYcited by 5

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

Large language models (LLMs) have demonstrated an impressive ability to role-play humans and replicate complex social dynamics. While large-scale social simulations are gaining increasing attention, they still face significant challenges, particularly regarding high time and computation costs. Existing solutions, such as distributed mechanisms or hybrid agent-based model (ABM) integrations, either fail to address inference costs or compromise accuracy and generalizability. To this end, we propose EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation. EcoLANG operates in two stages: (1) language evolution, where we filter synonymous words and optimize sentence-level rules through natural selection, and (2) language utilization, where agents in social simulations communicate using the evolved language. Experimental results demonstrate that EcoLANG reduces token consumption by over 20%, enhancing efficiency without sacrificing simulation accuracy.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 26 of its 55 references that are in the map. First posted on arXiv 11 May 2025.

Builds on

26 of 55 references.

Closest ancestors · 8

Same direction, newest first

  1. 2025SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users14 Apr
  2. 2025AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society12 Feb
  3. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents4 Dec
  4. 2024LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals15 Nov
  5. 2024Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation26 Feb
  6. 2023Simulating Opinion Dynamics with Networks of LLM-based Agents16 Nov
  7. 2023EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities16 Oct
  8. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 18

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2024The Llama 3 Herd of Modelscited by 14,715
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  5. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,808
  6. 2023ChatDev: Communicative Agents for Software Developmentcited by 919
  7. 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 752
  8. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 301
  9. 2023Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectivescited by 257
  10. 2020Emergent Multi-Agent Communication in the Deep Learning Eracited by 170
  11. 2017Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbolscited by 125
  12. 2017SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumourscited by 77
6 more
  1. 2020Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learningcited by 66
  2. 2024From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake Newscited by 51
  3. 2022Emergent Communication for Understanding Human Language Evolution: What's Missing?cited by 23
  4. 2024Very Large-Scale Multi-Agent Simulation in AgentScopecited by 18
  5. 2023#RoeOverturned: Twitter Dataset on the Abortion Rights Controversycited by 14
  6. 2024Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communicationcited by 14

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2026Linguistics and Human Brain: A Perspective of Computational Neurosciencecited by 4
  2. 2026HyLaT: Efficient Multi-Agent Communication via Hybrid Latent-Text Protocolcited by 4
  3. 2025Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changescited by 1
  4. 2026The Contagion Tensor: A Framework for Measuring Output-Distribution Coupling in Multi-Agent LLM Systems -- and Auditing the Claims It Enablescited by 0
  5. 2026Rethinking Multi-Agent Collaboration: When More Is Lesscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026AI Agents Alone Are Not (Yet) Sufficient for Social Simulation
  2. 2024Shall We Team Up: Exploring Spontaneous Cooperation of Competing LLM Agents
  3. 2024LLM-Augmented Agent-Based Modelling for Social Simulations: Challenges and Opportunities
  4. 2024GenSim: A General Social Simulation Platform with Large Language Model based Agents
  5. 2024Sense and Sensitivity: Evaluating the simulation of social dynamics via Large Language Models
  6. 2024AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior
  7. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agents
  8. 2026GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions