| Challenge: | Existing approaches to simulating language emergence among deep neural agents are challenging due to the discrete nature of communication. |
| Approach: | They propose a toolkit that greatly simplifies the implementation of emergent-language communication games. |
| Outcome: | The proposed toolkit simplifies the implementation of emergent-language communication games. |
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Emergent Language-Based Coordination In Deep Multi-Agent Systems (2022.emnlp-tutorials)
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| Challenge: | Pre-trained deep networks are the standard building blocks of modern AI applications. |
| Approach: | This tutorial will introduce deep net emergent communication and discuss current shortcomings . participants will implement and analyze two emergentic communication setups from the literature . |
| Outcome: | The presentation will cover various topics from the present and recent past, as well as discussing current shortcomings and suggest future directions. |
The Grammar of Emergent Languages (2020.emnlp-main)
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| Challenge: | Existing studies on emergent languages focus on semantics, but lack tools to analyse their properties. |
| Approach: | They propose to use unsupervised grammar induction techniques to analyse emergent languages and to examine their syntactic properties. |
| Outcome: | The proposed techniques are appropriate to analyse emergent languages and show that they exhibit syntactic properties similar to those observed in human language. |
Co-evolution of language and agents in referential games (2021.eacl-main)
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| Challenge: | Referential games allow neural agents to learn language, but they do not take into account the learning biases of the learners. |
| Approach: | They propose to model cultural and architectural evolution in a population of agents to take into account learning biases of the language learners and let them co-evolve. |
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A Combinatorial Approach to Neural Emergent Communication (2025.coling-main)
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| Challenge: | Existing research on emergent communication uses the Lewis signaling game . however, the training data is limited and the messages are often ineffective . |
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The Emergence of Compositional Languages in Multi-entity Referential Games: from Image to Graph Representations (2024.emnlp-main)
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| Challenge: | Language Emergence research uses jointly trained artificial agents to solve a task. |
| Approach: | They propose a multi-entity game in which targets include multiple entities that are spatially related. |
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Emergent Linguistic Phenomena in Multi-Agent Communication Games (D19-1)
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| Challenge: | a recent study examines the behavior of linguistic agents in a community-level setting . a linguistic continuum emerges where neighboring languages are more mutually intelligible than farther removed ones . |
| Approach: | They propose a multi-agent communication framework for studying linguistic phenomena at the community level. |
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How agents see things: On visual representations in an emergent language game (D18-1)
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| Challenge: | Existing studies focus on the agents’ symbol usage, rather than on their representation of visual input. |
| Approach: | They propose to use visual representations of objects to create language-like communication systems by integrating them with the visual input of a game. |
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So many design choices: Improving and interpreting neural agent communication in signaling games (2023.findings-acl)
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| Challenge: | Emergent language games are experimental protocols designed to model how communication may arise among a group of agents. |
| Approach: | They propose to adopt a signaling game in which a sender is exposed to an image and generates a sequence of symbols that is transmitted to a receiver. |
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Miss Tools and Mr Fruit: Emergent Communication in Agents Learning about Object Affordances (P19-1)
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| Challenge: | Recent research studies communication emergence in communities of deep network agents assigned a joint task . authors propose a game meeting many desiderata for a natural communication environment . |
| Approach: | They propose a task capturing aspects of the human environment and human conversation . they propose 'game' meeting many desiderata for a natural communication environment . |
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Searching for the Most Human-like Emergent Language (2025.emnlp-main)
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| Challenge: | Existing work on emergent communication systems to generate languages with high statistical similarity to human languages has not been done. |
| Approach: | They propose to optimize a signalling game-based emergent communication environment to generate state-of-the-art emergentic languages with a high degree of similarity to human language. |
| Outcome: | The proposed language generates state-of-the-art on XferBench benchmark, demonstrating its similarity to human language and entropy-minimization properties. |