Why Are Parsing Actions for Understanding Message Hierarchies Not Random?
Not on the map. Why?
Abstract (arXiv)
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 strategiesunicodex2013ones that deviate significantly from human language comprehensionunicodex2013can 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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 25 references that are in the map. First posted on arXiv 27 Jun 2025.
Builds on
14 of 25 references.
References · 14
- 2017Attention Is All You Needcited by 59,932
- 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
- 2020Emergent Multi-Agent Communication in the Deep Learning Eracited by 168
- 2017Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbolscited by 123
- 2020Compositionality and Generalization in Emergent Languagescited by 103
- 2018Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Inputcited by 102
- 2025Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corporacited by 86
- 2019Anti-efficient encoding in emergent communicationcited by 59
- 2015Learning to Transduce with Unbounded Memorycited by 54
- 2019Learning Hierarchical Priors in VAEscited by 53
- 2022Emergent Communication: Generalization and Overfitting in Lewis Gamescited by 28
- 2024A Review of the Applications of Deep Learning-Based Emergent Communicationcited by 17
2 more
- 2024Emergent Language: A Survey and Taxonomycited by 12
- 2023Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segmentscited by 11
Built on by
Not cited yet.