1 code implementation • 28 May 2023 • Hwaran Lee, Seokhee Hong, Joonsuk Park, Takyoung Kim, Gunhee Kim, Jung-Woo Ha
Large language models (LLMs) learn not only natural text generation abilities but also social biases against different demographic groups from real-world data.
1 code implementation • 28 May 2023 • Hwaran Lee, Seokhee Hong, Joonsuk Park, Takyoung Kim, Meeyoung Cha, Yejin Choi, Byoung Pil Kim, Gunhee Kim, Eun-Ju Lee, Yong Lim, Alice Oh, Sangchul Park, Jung-Woo Ha
The potential social harms that large language models pose, such as generating offensive content and reinforcing biases, are steeply rising.
1 code implementation • 24 May 2023 • Taehyun Lee, Seokhee Hong, Jaewoo Ahn, Ilgee Hong, Hwaran Lee, Sangdoo Yun, Jamin Shin, Gunhee Kim
Based on \citet{Kirchenbauer2023watermark}, we propose a new watermarking method, Selective WatErmarking via Entropy Thresholding (SWEET), that promotes "green" tokens only at the position with high entropy of the token distribution during generation, thereby preserving the correctness of the generated code.
no code implementations • NAACL 2021 • Byeongchang Kim, Hyunwoo Kim, Seokhee Hong, Gunhee Kim
In this work, we ask: How robust are fact checking systems on claims in colloquial style?