تقرير
Computational Language Acquisition with Theory of Mind
| العنوان: | Computational Language Acquisition with Theory of Mind |
|---|---|
| المؤلفون: | Liu, Andy, Zhu, Hao, Liu, Emmy, Bisk, Yonatan, Neubig, Graham |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Artificial Intelligence |
| الوصف: | Unlike current state-of-the-art language models, young children actively acquire language through interactions with their surrounding environment and caretakers. One mechanism that has been argued to be critical to language learning is the ability to infer the mental states of other agents in social environments, coined Theory of Mind (ToM) by Premack & Woodruff (1978). Drawing inspiration from the modern operationalized versions of ToM implemented in Rabinowitz et al. (2018) and Zhu et al. (2021), we build language-learning agents equipped with ToM, and measure its effects on the learning process. We model ToM by giving the speaker agent an internal listener model that is trained alongside the speaker and used to rerank potential utterances. We experiment with varying task difficulty, hypothesizing that models will acquire more complex language to adapt to stronger environmental pressures. We find that training speakers with a highly weighted ToM listener component leads to performance gains in our image referential game setting. We also find some evidence that increasing task difficulty in the training process results in more fluent and precise utterances in evaluation. This suggests the potential utility of further incorporating ToM, as well as other insights from child language acquisition, into computational models of language acquisition. Comment: 9 pages, 3 figures. To be published in the 11th International Conference on Learning Representations, ICLR 2023, Conference Track Proceedings |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2303.01502 |
| رقم الأكسشن: | edsarx.2303.01502 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |