6 citations · 14 across the 17 of their papers we have counts for
4 papers · 1 filter
Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification
Runa Yoshida, Kosuke Nishida, Kyosuke Nishida
The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning capability of LLMs, we clarify…
CMDR: Contextual Multimodal Document Retrieval
Ryota Tanaka, Taku Hasegawa, Kyosuke Nishida
Multimodal document retrieval aims to retrieve relevant pages while preserving both textual and visual content from the original document. However, existing benchmarks primarily ev…
Debiasing Reward Models via Causally Motivated Inference-Time Intervention
Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida
Reward models (RMs) play a central role in aligning large language models (LLMs) with human preferences. However, RMs are often sensitive to spurious features such as response leng…
Responses Fall Short of Understanding: Revealing the Gap between Internal Representations and Responses in Visual Document Understanding
Haruka Kawasaki, Ryota Tanaka, Kyosuke Nishida
Visual document understanding (VDU) is a challenging task for large vision language models (LVLMs), requiring the integration of visual perception, text recognition, and reasoning…