11 citations · 18 across the 4 of their papers we have counts for
4 papers
Probability Bounding: Post-Hoc Calibration via Box-Constrained Softmax
Kyohei Atarashi, Satoshi Oyama, Hiromi Arai +1
Many studies have observed that modern neural networks achieve high accuracy while producing poorly calibrated probabilities, making calibration a critical practical issue. In this…
JBBQ: Japanese Bias Benchmark for Analyzing Social Biases in Large Language Models
Hitomi Yanaka, Namgi Han, Ryoma Kumon +5
With the development of large language models (LLMs), social biases in these LLMs have become a pressing issue. Although there are various benchmarks for social biases across langu…
Fair Machine Guidance to Enhance Fair Decision Making in Biased People
Mingzhe Yang, Hiromi Arai, Naomi Yamashita +1
Teaching unbiased decision-making is crucial for addressing biased decision-making in daily life. Although both raising awareness of personal biases and providing guidance on unbia…
Will Large-scale Generative Models Corrupt Future Datasets?
Ryuichiro Hataya, Han Bao, Hiromi Arai
Recently proposed large-scale text-to-image generative models such as DALLE 2, Midjourney, and StableDiffusion can generate high-quality and realistic images from users' pro…