1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought
Shin'ya Yamaguchi, Kosuke Nishida, Daiki Chijiwa
Large vision-language models (LVLMs) have demonstrated remarkable capabilities by integrating pre-trained vision encoders with large language models (LLMs). Similar to single-modal…
cs.LG2025
Zero-shot Concept Bottleneck Models
Shin'ya Yamaguchi, Kosuke Nishida, Daiki Chijiwa +1
Concept bottleneck models (CBMs) are inherently interpretable and intervenable neural network models, which explain their final label prediction by the intermediate prediction of h…
cs.AI2024★ 1 cited
Explanation Bottleneck Models
Shin'ya Yamaguchi, Kosuke Nishida
Recent concept-based interpretable models have succeeded in providing meaningful explanations by pre-defined concept sets. However, the dependency on the pre-defined concepts restr…