1 code implementation • 16 Dec 2021 • Hyunjae Kim, Jaehyo Yoo, Seunghyun Yoon, Jinhyuk Lee, Jaewoo Kang
Surprisingly, on NCBI-disease, our model achieves 75. 5 F1 score and even outperforms the previous best weakly supervised model by 4. 1 F1 score, which utilizes a rich in-domain dictionary provided by domain experts.
2 code implementations • 1 Jul 2020 • Minbyul Jeong, Mujeen Sung, Gangwoo Kim, Donghyeon Kim, Wonjin Yoon, Jaehyo Yoo, Jaewoo Kang
We observe that BioBERT trained on the NLI dataset obtains better performance on Yes/No (+5. 59%), Factoid (+0. 53%), List type (+13. 58%) questions compared to performance obtained in a previous challenge (BioASQ 7B Phase B).
no code implementations • 13 Sep 2019 • Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, Jaegul Choo
Attention networks, a deep neural network architecture inspired by humans' attention mechanism, have seen significant success in image captioning, machine translation, and many other applications.