4 papers
Non-Autoregressive Minimum Bayes' Risk Decoding for Fast Speech Recognition
Hiroyuki Deguchi, Takatomo Kano, Katsuki Chousa +1
Non-autoregressive (NAR) decoding generates output tokens in parallel, making speech recognition faster than autoregressive decoding, which generates them sequentially from left to…
One Single Hub Text Breaks CLIP: Identifying Vulnerabilities in Cross-Modal Encoders via Hubness
Hiroyuki Deguchi, Katsuki Chousa, Yusuke Sakai
The hubness problem, in which hub embeddings are close to many unrelated examples, occurs often in high-dimensional embedding spaces and may pose a practical threat for purposes su…
Hacking Neural Evaluation Metrics with Single Hub Text
Hiroyuki Deguchi, Katsuki Chousa, Yusuke Sakai
Strongly human-correlated evaluation metrics serve as an essential compass for the development and improvement of generation models and must be highly reliable and robust. Recent e…
JaParaPat: A Large-Scale Japanese-English Parallel Patent Application Corpus
Masaaki Nagata, Katsuki Chousa, Norihito Yasuda
We constructed JaParaPat (Japanese-English Parallel Patent Application Corpus), a bilingual corpus of more than 300 million Japanese-English sentence pairs from patent applications…