Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Do, Hyo Jin"'
Autor:
Do, Hyo Jin, Ostrand, Rachel, Weisz, Justin D., Dugan, Casey, Sattigeri, Prasanna, Wei, Dennis, Murugesan, Keerthiram, Geyer, Werner
While humans increasingly rely on large language models (LLMs), they are susceptible to generating inaccurate or false information, also known as "hallucinations". Technical advancements have been made in algorithms that detect hallucinated content b
Externí odkaz:
http://arxiv.org/abs/2405.20434
Autor:
Paes, Lucas Monteiro, Wei, Dennis, Do, Hyo Jin, Strobelt, Hendrik, Luss, Ronny, Dhurandhar, Amit, Nagireddy, Manish, Ramamurthy, Karthikeyan Natesan, Sattigeri, Prasanna, Geyer, Werner, Ghosh, Soumya
Perturbation-based explanation methods such as LIME and SHAP are commonly applied to text classification. This work focuses on their extension to generative language models. To address the challenges of text as output and long text inputs, we propose
Externí odkaz:
http://arxiv.org/abs/2403.14459
Autor:
Do, Hyo Jin, Choi, Ho-Jin
Publikováno v:
Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation. :142-150
Autor:
Do, Hyo Jin, Choi, Ho-Jin
Publikováno v:
2015 International Conference on Big Data & Smart Computing (BIGCOMP); 2015, p39-42, 4p
Autor:
Do, Hyo Jin, Fu, Wai-Tat
Publikováno v:
2016 IEEE International Conference on Healthcare Informatics (ICHI); 2016, p318-318, 1p