Lupinus Inc. (Headquarters: Minato-ku, Tokyo; President and CEO: Hiroki Sano, hereinafter "the Company") is pleased to announce that, as part of a joint research project with JCOM Corporation (Headquarters: Chiyoda-ku, Tokyo; President and CEO: Yoichi Iwaki, hereinafter "J:COM"), they developed a question category classification method combining Contextual Bandit and LLM-as-a-Judge. This was presented orally at the 40th Annual Conference of the Japanese Society for Artificial Intelligence, held from June 8 (Mon) to June 12 (Fri), 2026, at G Messe Gunma in Takasaki City, Gunma Prefecture. The Company will continue to contribute to the improvement of service quality utilizing AI through technological cooperation with partner companies, including J:COM. ■ Presentation Overview Conference Name The 40th Annual Conference of the Japanese Society for Artificial Intelligence Date June 8 (Mon) - June 12 (Fri), 2026 Venue G Messe Gunma, Takasaki City, Gunma Prefecture Presentation Title Question Category Classification Combining Contextual Bandit and LLM-as-a-Judge Presenters Katsuya Wada (Company), Shohei Kibe (Company), Reon Hata (J:COM) Presentation Format Oral Presentation ■ Background and Objectives [Social Background] In recent years, with the widespread adoption of AI-powered conversational systems, the importance of appropriately responding to diverse user inquiries has been increasing. Especially in services with frequent customer touchpoints, a wide variety of inquiries are received daily, including those with different phrasing and notation. In cable TV and telecommunications services like J:COM, there are many users aged 60 and over, requiring the appropriate understanding of intent for diverse inquiries from a broad range of users. In such an environment, the accuracy of distinguishing between "questions requiring a search" and "conversational responses" in conversational systems incorporating RAG is directly linked to response quality and processing efficiency.