no code implementations • 2 Jun 2021 • Zhe Liu, Yufan Guo, Jalal Mahmud
Although deep neural networks have been widely employed and proven effective in sentiment analysis tasks, it remains challenging for model developers to assess their models for erroneous predictions that might exist prior to deployment.
no code implementations • NAACL 2021 • Zhe Liu, Yufan Guo, Jalal Mahmud
Although deep neural networks have been widely employed and proven effective in sentiment analysis tasks, it remains challenging for model developers to assess their models for erroneous predictions that might exist prior to deployment.
no code implementations • WS 2020 • Olga Kovaleva, Chaitanya Shivade, Satyan Kashyap, a, Karina Kanjaria, Joy Wu, Deddeh Ballah, Adam Coy, Alex Karargyris, ros, Yufan Guo, David Beymer Beymer, Anna Rumshisky, V Mukherjee, ana Mukherjee
Using MIMIC-CXR, an openly available database of chest X-ray images, we construct both a synthetic and a real-world dataset and provide baseline scores achieved by state-of-the-art models.
no code implementations • 5 Sep 2018 • Mehdi Moradi, Ali Madani, Yaniv Gur, Yufan Guo, Tanveer Syeda-Mahmood
The source of big data is typically large image collections and clinical reports recorded for these images.
no code implementations • 1 Nov 2017 • Yiding Lu, Yufan Guo, Anna Korhonen
Conclusion: This demonstrates that approaches purely based on network topology provide a more suitable approach to DTI prediction in the many real-life situations where little or no prior knowledge is available about the characteristics of drugs, targets, or their interactions.
no code implementations • 9 Oct 2015 • Simon Baker, Ilona Silins, Yufan Guo, Imran Ali, Johan Högberg, Ulla Stenius, Anna Korhonen
The hallmarks of cancer have become highly influential in cancer research.
no code implementations • TACL 2015 • Yufan Guo, Roi Reichart, Anna Korhonen
Inferring the information structure of scientific documents is useful for many NLP applications.
no code implementations • LREC 2014 • Xiao Jiang, Yufan Guo, Jeroen Geertzen, Dora Alexopoulou, Lin Sun, Anna Korhonen
Native Language Identification (NLI) is a task aimed at determining the native language (L1) of learners of second language (L2) on the basis of their written texts.
BIG-bench Machine Learning
Native Language Identification
+1