Recommendations for Systematic Research on Emergent Language
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Abstract (arXiv)
Emergent language is unique among fields within the discipline of machine learning for its open-endedness, not obviously presenting well-defined problems to be solved. As a result, the current research in the field has largely been exploratory: focusing on establishing new problems, techniques, and phenomena. Yet after these problems have been established, subsequent progress requires research which can measurably demonstrate how it improves on prior approaches. This type of research is what we call systematic research; in this paper, we illustrate this mode of research specifically for emergent language. We first identify the overarching goals of emergent language research, categorizing them as either science or engineering. Using this distinction, we present core methodological elements of science and engineering, analyze their role in current emergent language research, and recommend how to apply these elements.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 32 references that are in the map. First posted on arXiv 22 Jun 2022.
Builds on
21 of 32 references.
References · 21
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- 2019Anti-efficient encoding in emergent communicationcited by 59
- 2019Biases for Emergent Communication in Multi-agent Reinforcement Learningcited by 48
9 more
- 2018How agents see things: On visual representations in an emergent language gamecited by 45
- 2019EGG: a toolkit for research on Emergence of lanGuage in Gamescited by 42
- 2019Emergent Linguistic Phenomena in Multi-Agent Communication Gamescited by 36
- 2019Capacity, Bandwidth, and Compositionality in Emergent Language Learningcited by 30
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- 2020Emergent Communication Pretraining for Few-Shot Machine Translationcited by 13
- 2019Developmentally motivated emergence of compositional communication via template transfercited by 8
- 2020Inductive Bias and Language Expressivity in Emergent Communicationcited by 6
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.