# Internal and external pressures on language emergence: least effort, object constancy and frequency

arXiv: https://arxiv.org/abs/2004.03868 · HTML: https://mlsanity.com/paper/2004.03868/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2020.

## Built on by (most cited first, 13 of 13)

- [Visually Grounded Reasoning across Languages and Cultures](https://mlsanity.com/paper/2109.13238/) (2021)
- [Emergent Communication of Generalizations](https://mlsanity.com/paper/2106.02668/) (2021)
- [Linking Emergent and Natural Languages via Corpus Transfer](https://mlsanity.com/paper/2203.13344/) (2022)
- [A Review of the Applications of Deep Learning-Based Emergent Communication](https://mlsanity.com/paper/2407.03302/) (2024)
- [Emergent Language: A Survey and Taxonomy](https://mlsanity.com/paper/2409.02645/) (2024)
- [Emergence of hierarchical reference systems in multi-agent communication](https://mlsanity.com/paper/2203.13176/) (2022)
- [Towards Interactive Language Modeling](https://mlsanity.com/paper/2112.11911/) (2021)
- [ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation](https://mlsanity.com/paper/2310.11282/) (2023)
- [Mathematically Modeling the Lexicon Entropy of Emergent Language](https://mlsanity.com/paper/2211.15783/) (2022)
- [Emergent Communication with Attention](https://mlsanity.com/paper/2305.10920/) (2023)
- [ELCC: the Emergent Language Corpus Collection](https://mlsanity.com/paper/2407.04158/) (2024)
- [Contrastive Multimodal Learning for Emergence of Graphical Sensory-Motor Communication](https://mlsanity.com/paper/2210.06468/) (2022)
- [A Compressive-Expressive Communication Framework for Compositional Representations](https://mlsanity.com/paper/2501.19182/) (2025)

## Abstract (arXiv)

In previous work, artificial agents were shown to achieve almost perfect accuracy in referential games where they have to communicate to identify images. Nevertheless, the resulting communication protocols rarely display salient features of natural languages, such as compositionality. In this paper, we propose some realistic sources of pressure on communication that avert this outcome. More specifically, we formalise the principle of least effort through an auxiliary objective. Moreover, we explore several game variants, inspired by the principle of object constancy, in which we alter the frequency, position, and luminosity of the objects in the images. We perform an extensive analysis on their effect through compositionality metrics, diagnostic classifiers, and zero-shot evaluation. Our findings reveal that the proposed sources of pressure result in emerging languages with less redundancy, more focus on high-level conceptual information, and better abilities of generalisation. Overall, our contributions reduce the gap between emergent and natural languages.