mlsanityData to 14 Oct 2026

Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication

arXiv 2406.07277 ↗First posted 11 Jun 2024cs.CL cs.AI cs.MAcited by 3

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Abstract (arXiv)

Effective communication requires the ability to refer to specific parts of an observation in relation to others. While emergent communication literature shows success in developing various language properties, no research has shown the emergence of such positional references. This paper demonstrates how agents can communicate about spatial relationships within their observations. The results indicate that agents can develop a language capable of expressing the relationships between parts of their observation, achieving over 90% accuracy when trained in a referential game which requires such communication. Using a collocation measure, we demonstrate how the agents create such references. This analysis suggests that agents use a mixture of non-compositional and compositional messages to convey spatial relationships. We also show that the emergent language is interpretable by humans. The translation accuracy is tested by communicating with the receiver agent, where the receiver achieves over 78% accuracy using parts of this lexicon, confirming that the interpretation of the emergent language was successful.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 31 references that are in the map. First posted on arXiv 11 Jun 2024.

Builds on

15 of 31 references.

References · 15

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3 more
  1. 2020Measuring non-trivial compositionality in emergent communicationcited by 10
  2. 2020Rat big, cat eaten! Ideas for a useful deep-agent protolanguagecited by 4
  3. 2021Neural networks can understand compositional functions that humans do not, in the context of emergent communicationcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.