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20172026
most citedEfficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention

289 citations · 309 across the 7 of their papers we have counts for

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cs.CL2026

LLM-jp-4 Technical Report

LLM-jp, :, Chaoran Liu +16

This paper presents LLM-jp-4, a family of Japanese sovereign large language models (LLMs) developed with an emphasis on transparency, reproducibility, and practical usability. LLM-…

cs.CL2025

BIS Reasoning 1.0: The First Large-Scale Japanese Benchmark for Belief-Inconsistent Syllogistic Reasoning

Ha-Thanh Nguyen, Hideyuki Tachibana, Chaoran Liu +4

We present BIS Reasoning 1.0, the first large-scale Japanese dataset of syllogistic reasoning problems explicitly designed to evaluate belief-inconsistent reasoning in large langua…

cs.CL2025

RAD: Redundancy-Aware Distillation for Hybrid Models via Self-Speculative Decoding

Yuichiro Hoshino, Hideyuki Tachibana, Muneyoshi Inahara +1

Hybrid models combining Transformers and State Space Models (SSMs) are promising for balancing performance and efficiency. However, optimizing these hybrid models, particularly by…

cs.CL2024

Multilingual Sentence-T5: Scalable Sentence Encoders for Multilingual Applications

Chihiro Yano, Akihiko Fukuchi, Shoko Fukasawa +2

Prior work on multilingual sentence embedding has demonstrated that the efficient use of natural language inference (NLI) data to build high-performance models can outperform conve…

cs.CL2020★ 2 cited

Accent Estimation of Japanese Words from Their Surfaces and Romanizations for Building Large Vocabulary Accent Dictionaries

Hideyuki Tachibana, Yotaro Katayama

In Japanese text-to-speech (TTS), it is necessary to add accent information to the input sentence. However, there are a limited number of publicly available accent dictionaries, an…