25 citations · 25 across the 9 of their papers we have counts for
9 papers
Towards Cognitive Process-Aware Proactive Writing Support
Masahiro Yoshida, Atsuya Kobayashi, Kei Tateno +1
Large language models can support writing, but existing tools require users to explicitly articulate prompts-particularly burdensome in creative writing, where intentions are often…
Offline Contextual Bandits in the Presence of New Actions
Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura +6
Automated decision-making algorithms drive applications such as recommendation systems and search engines. These algorithms often rely on off-policy contextual bandits or off-polic…
PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows
Kazuki Kawamura, Satoshi Waki, Kei Tateno
Multi-agent LLM workflows -- systems composed of multiple role-specific LLM calls -- often outperform single-prompt baselines, but they remain difficult to debug and refine. Failur…
Off-Policy Evaluation for Ranking Policies under Deterministic Logging Policies
Koichi Tanaka, Kazuki Kawamura, Takanori Muroi +6
Off-Policy Evaluation (OPE) is an important practical problem in algorithmic ranking systems, where the goal is to estimate the expected performance of a new ranking policy using o…
LoopLens: Supporting Search as Creation in Loop-Based Music Composition
Sheng Long, Atsuya Kobayashi, Kei Tateno
Creativity support tools (CSTs) typically frame search as information retrieval, yet in practices like electronic dance music production, search serves as a creative medium for col…
Safely Exploring Novel Actions in Recommender Systems via Deployment-Efficient Policy Learning
Haruka Kiyohara, Yusuke Narita, Yuta Saito +2
In many real recommender systems, novel items are added frequently over time. The importance of sufficiently presenting novel actions has widely been acknowledged for improving lon…