activity
20232025
most citedEmpirical Analysis of the Inductive Bias of Recurrent Neural Networks by Discrete Fourier Transform of Output Sequences

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Why Are Parsing Actions for Understanding Message Hierarchies Not Random?

Daichi Kato, Ryo Ueda, Yusuke Miyao

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 hiera…

cs.CL2024

Emergent Word Order Universals from Cognitively-Motivated Language Models

Tatsuki Kuribayashi, Ryo Ueda, Ryo Yoshida +3

The world's languages exhibit certain so-called typological or implicational universals; for example, Subject-Object-Verb (SOV) languages typically use postpositions. Explaining th…

cs.CL2023★ 2 cited

Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments

Ryo Ueda, Tadahiro Taniguchi

As a sub-discipline of evolutionary and computational linguistics, emergent communication (EC) studies communication protocols, called emergent languages, arising in simulations wh…

cs.CL2023

Emergent Communication with Attention

Ryokan Ri, Ryo Ueda, Jason Naradowsky

To develop computational agents that better communicate using their own emergent language, we endow the agents with an ability to focus their attention on particular concepts in th…

cs.LG2023★ 2 cited

Empirical Analysis of the Inductive Bias of Recurrent Neural Networks by Discrete Fourier Transform of Output Sequences

Taiga Ishii, Ryo Ueda, Yusuke Miyao

A unique feature of Recurrent Neural Networks (RNNs) is that it incrementally processes input sequences. In this research, we aim to uncover the inherent generalization properties,…