3 citations · 3 across the 5 of their papers we have counts for
6 papers
Where the Evidence Lives: Auditing AI Companions' Self-Descriptions
Seiya Ikeda, Shin-nosuke Ishikawa
Companion agents describe themselves: they remember, they understand their users, the relationship has changed them. We argue that such accounts, and the experience ratings that se…
When AI Says It Feels
Shin-nosuke Ishikawa, Seiya Ikeda, Hirotsugu Ohba
Large language models (LLMs) are generally constrained from expressing feelings through human-preference alignment in post-training processes. This policy is designed using a top-d…
The Idola Tribus of AI: Large Language Models tend to perceive order where none exists
Shin-nosuke Ishikawa, Masato Todo, Taiki Ogihara +1
We present a tendency of large language models (LLMs) to generate absurd patterns despite their clear inappropriateness in a simple task of identifying regularities in number serie…
AI with Emotions: Exploring Emotional Expressions in Large Language Models
Shin-nosuke Ishikawa, Atsushi Yoshino
The human-level performance of Large Language Models (LLMs) across various tasks has raised expectations for the potential of Artificial Intelligence (AI) to possess emotions somed…
Example-Based Explainable AI and its Application for Remote Sensing Image Classification
Shin-nosuke Ishikawa, Masato Todo, Masato Taki +5
We present a method of explainable artificial intelligence (XAI), "What I Know (WIK)", to provide additional information to verify the reliability of a deep learning model by showi…
Mechanism of proton- elastic backward scattering at intermediate energy
A. P. Kobushkin, E. A. Strokovsky, K. Hatanaka +1
We provide systematic analysis of the differential cross section of the proton- elastic scattering at and at MeV. Three mechanisms ar…