Abstract
If humans understood language by randomly selecting parsing actions, it might have been necessary to construct a robust symbolic system capable of being interpreted under any hierarchical structure. However, human parsing strategies do not seem to follow such a random pattern. Why is that the case? In fact, a previous study on emergent communication using models with hierarchical biases have reported that agents adopting random parsing strategies$\unicode{x2013}$ones that deviate significantly from human language comprehension$\unicode{x2013}$can achieve high communication accuracy. In this study, we investigate this issue by making two simple and natural modifications to the experimental setup: (I) we use more complex inputs that have hierarchical structures, such that random parsing makes semantic interpretation more difficult, and (II) we incorporate a surprisal-related term, which is known to influence the order of words and characters in natural language, into the objective function. With these changes, we evaluate whether agents employing random parsing strategies still maintain high communication accuracy.
Abstract (translated)
如果人类通过随机选择解析动作来理解语言，那么可能需要构建一个能够在任何层次结构下被解释的稳健符号系统。然而，人类的解析策略似乎并不遵循这种随机模式。这是为什么呢？事实上，以前使用具有层级偏好的模型进行新兴交流的研究报告指出，采用随机解析策略的代理——这些策略与人类语言理解显著不同——可以达到很高的通信准确性。在本研究中，我们通过对实验设置作出两个简单而自然的修改来探讨这个问题：（I）我们使用具有层次结构的更复杂的输入，使得随机解析使语义解释变得更加困难；（II）我们在目标函数中加入了与惊讶度相关的项，这是已知会影响自然语言单词和字符顺序的因素。通过这些变化，我们评估采用随机解析策略的代理是否仍然保持高通信准确性。
URL
https://arxiv.org/abs/2506.22366
