2 citations · 3 across the 3 of their papers we have counts for
3 papers
Metropolis-Hastings Captioning Game: Knowledge Fusion of Vision Language Models via Decentralized Bayesian Inference
Yuta Matsui, Ryosuke Yamaki, Ryo Ueda +2
We propose the Metropolis-Hastings Captioning Game (MHCG), a method to fuse knowledge of multiple vision-language models (VLMs) by learning from each other. Although existing metho…
Pointing out Human Answer Mistakes in a Goal-Oriented Visual Dialogue
Ryosuke Oshima, Seitaro Shinagawa, Hideki Tsunashima +2
Effective communication between humans and intelligent agents has promising applications for solving complex problems. One such approach is visual dialogue, which leverages multimo…
Modeling Multiple User Interests using Hierarchical Knowledge for Conversational Recommender System
Yuka Okuda, Katsuhito Sudoh, Seitaro Shinagawa +1
A conversational recommender system (CRS) is a practical application for item recommendation through natural language conversation. Such a system estimates user interests for appro…