3 papers
cs.CL2026
Evaluating the Robustness of Japanese LLMs to IME-Related and Typographical Errors
Ryota Mibayashi, Hiroaki Ohshima
Large language models (LLMs) have achieved strong performance across various natural language processing tasks. However, their robustness to typographical errors remains underexplo…
cs.MM2026
Supporting Perspective Acquisition and Opinion Formation on Societal Issues Through AI-Generated Japanese Rap Battle Debates
Ryota Mibayashi, Toru Urakawa, Dai Takanashi +9
Acquiring diverse perspectives and forming informed opinions on societal issues are essential for critical thinking and informed decision-making. Although observing debates between…
cs.IR2025
Effect of Model Merging in Domain-Specific Ad-hoc Retrieval
Taiga Sasaki, Takehiro Yamamoto, Hiroaki Ohshima +1
In this study, we evaluate the effect of model merging in ad-hoc retrieval tasks. Model merging is a technique that combines the diverse characteristics of multiple models. We hypo…