4 papers
A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
Lixin Xiu, Xufang Luo, Hideki Nakayama
Large vision-language models (LVLMs) achieve impressive performance, yet their internal decision-making processes remain opaque, making it difficult to determine if the success ste…
Follow-Your-Preference: Towards Preference-Aligned Image Inpainting
Yutao Shen, Junkun Yuan, Toru Aonishi +2
This paper investigates image inpainting with preference alignment. Instead of introducing a novel method, we go back to basics and revisit fundamental problems in achieving such a…
BrainCodec: Neural fMRI codec for the decoding of cognitive brain states
Yuto Nishimura, Masataka Sawayama, Ayumu Yamashita +2
Recently, leveraging big data in deep learning has led to significant performance improvements, as confirmed in applications like mental state decoding using fMRI data. However, fM…
HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis
Yuto Nishimura, Takumi Hirose, Masanari Ohi +2
Recently, Text-to-speech (TTS) models based on large language models (LLMs) that translate natural language text into sequences of discrete audio tokens have gained great research…