# SIGN: Schema-Induced Games for Naming

arXiv: https://arxiv.org/abs/2510.21855 · HTML: https://mlsanity.com/paper/2510.21855/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 2 references that are in the map.
- First posted on arXiv 22 Oct 2025.

## Builds on (most cited first, 1 of 1)

- [Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication](https://mlsanity.com/paper/2402.18439/) (2024)

## Built on by (most cited first, 1 of 1)

- [Microscopic dynamics of consensus formation in multi-agent LLM Naming Games](https://mlsanity.com/paper/2608.02178/) (2026)

## Abstract (arXiv)

Real-world AI systems are tackling increasingly complex problems, often through interactions among large language model (LLM) agents. When these agents develop inconsistent conventions, coordination can break down. Applications such as collaborative coding and distributed planning therefore require reliable, consistent communication, and scalability is a central concern as systems grow. We introduce Schema-Induced Games for Naming (SIGN), a naming game that examines how lightweight structure can steer convention formation. We compare schema-induced communication to unconstrained natural language and find faster convergence with up to 5.8x higher agreement. These results suggest that minimal structure can act as a simple control knob for efficient multi-agent coordination, pointing toward broader applications beyond the naming game.