论文标题
参考：（视觉）参考游戏中语言出现和接地的命名法和框架
ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games
论文作者
论文摘要
自然语言是人类拥有的强大工具，可以传达信息并朝着共同的目标进行合作。它们的价值在于一些主要属性，例如构图，层次结构和经常性语法，计算语言学家一直在研究语言游戏引起的人造语言的出现。直到最近，AI社区才开始调查语言的出现和扎根，旨在朝着更好的人类机器界面努力。例如，能够将其愿景与正在进行的对话联系起来的交互式/对话式AI助手。 本文为该研究领域提供了两种贡献。首先，提出了一个命名法，以了解研究语言出现和基础的主要举措，从而解决了假设和约束的变化。其次，引入了一个基于Pytorch的深度学习框架，标题为“参考”，该框架致力于进一步探索语言出现和基础。通过提供主要算法和指标的基线实现，除了许多不同的功能和方法之外，参考gym试图简化该领域的进入障碍并为社区提供共同的实现。
Natural languages are powerful tools wielded by human beings to communicate information and co-operate towards common goals. Their values lie in some main properties like compositionality, hierarchy and recurrent syntax, which computational linguists have been researching the emergence of in artificial languages induced by language games. Only relatively recently, the AI community has started to investigate language emergence and grounding working towards better human-machine interfaces. For instance, interactive/conversational AI assistants that are able to relate their vision to the ongoing conversation. This paper provides two contributions to this research field. Firstly, a nomenclature is proposed to understand the main initiatives in studying language emergence and grounding, accounting for the variations in assumptions and constraints. Secondly, a PyTorch based deep learning framework is introduced, entitled ReferentialGym, which is dedicated to furthering the exploration of language emergence and grounding. By providing baseline implementations of major algorithms and metrics, in addition to many different features and approaches, ReferentialGym attempts to ease the entry barrier to the field and provide the community with common implementations.
