Katsuki Chousa
2 indexed papers
Publications per year
Top categories
Frequent co-authors
Research Timeline
The paper proposes a method to identify 'hub texts' that exploit vulnerabilities in cross-modal encoders, demonstrating that a single text can achieve unrealistically high similarity scores across diverse images in tasks like image captioning and retrieval.
This paper proposes a novel non-autoregressive (NAR) decoding framework based on minimum Bayes' risk (MBR) for speech recognition, which outperforms previous NAR decoding and runs faster than autoregressive decoding.
Papers
Non-Autoregressive Minimum Bayes' Risk Decoding for Fast Speech Recognition
This paper proposes a novel non-autoregressive (NAR) decoding framework based on minimum Bayes' risk (MBR) for speech recognition, which outperforms previous NAR decoding and runs faster than autoregr…