2 citations · 2 across the 8 of their papers we have counts for
10 papers
Improving the Diversity of LLM Outputs without a Trade-off
Ryoma Sato
We propose DAST (Diversifying Arithmetic Sampling with TokenTour), a method that increases the diversity of LLM outputs without any change to the marginal distribution and with neg…
AgentRecommender: LLM Agents Enable Customizable Recommender Systems on the User Side
Ryoma Sato
Recommender systems have traditionally been developed for platforms. However, this has given rise to many phenomena that may be advantageous for platform lock-in but are a nuisance…
Even GPT-5.2 Can't Count to Five: The Case for Zero-Error Horizons in Trustworthy LLMs
Ryoma Sato
We propose Zero-Error Horizon (ZEH) for trustworthy LLMs, which represents the maximum range that a model can solve without any errors. While ZEH itself is simple, we demonstrate t…
Interestingness First Classifiers
Ryoma Sato
Most machine learning models are designed to maximize predictive accuracy. In this work, we explore a different goal: building classifiers that are interesting. An ``interesting cl…
Solving the Cold Start Problem on One's Own as an End User via Preference Transfer
Ryoma Sato
We propose a new approach that enables end users to directly solve the cold start problem by themselves. The cold start problem is a common issue in recommender systems, and many m…
Overhead-free User-side Recommender Systems
Ryoma Sato
Traditionally, recommendation algorithms have been designed for service developers. But recently, a new paradigm called user-side recommender systems has been proposed. User-side r…
Training-free Graph Neural Networks and the Power of Labels as Features
Ryoma Sato
We propose training-free graph neural networks (TFGNNs), which can be used without training and can also be improved with optional training, for transductive node classification. W…
User-Side Realization
Ryoma Sato
Users are dissatisfied with services. Since the service is not tailor-made for a user, it is natural for dissatisfaction to arise. The problem is, that even if users are dissatisfi…
Making Translators Privacy-aware on the User's Side
Ryoma Sato
We propose PRISM to enable users of machine translation systems to preserve the privacy of data on their own initiative. There is a growing demand to apply machine translation syst…
Advancing AI Audits for Enhanced AI Governance
Arisa Ema, Ryo Sato, Tomoharu Hase +3
As artificial intelligence (AI) is integrated into various services and systems in society, many companies and organizations have proposed AI principles, policies, and made the rel…