… architecture, hierarchical architecture, modular architecture, and generative adversarial …
using the parallel feature sharing MTL architecture. He et al. [47] learn the aspect term extraction …

… structure to model the conditional relations between three subtasks and to effectively extract
textual … The multi-task learning phase can be further decomposed into learning two single …

… 1) We propose a multi-task learning (MTL) framework for relation extraction that exploits the
… multi-task model is more potent in extracting interacted protein pairs over the architecture …

… for spreadsheet semantic structure extraction. First, we propose a multi-task framework that
learns … Our evaluation shows that our proposed multi-task framework is highly effective that …

… limitations and propose a multi-task learning framework for the … Subsequently, the architecture
utilizes a CNN framework to … Experimental results suggest that the proposed multi-task …

… Many works of literature have also proved that LSTM can effectively extract text semantic …
structure of the model clearer, we did not give the details of the adversarial multi-task …

… However, our argument pair extraction task focuses more on the internal structure and
relations between reviews and rebuttals. In addition, the size of our dataset is much larger than …

… a multi-task deep neural network architecture … extract innovative ideas and identify new use
cases for product development. We visualise and interpret the clusters of keywords extracted …

… This paper proposes a novel multi-task learning framework that unifies explicit and implicit
aspect identification into a single model. The framework uses a BERT-based backbone with …

… The multi-task learning module does not need to directly change the network structure of
the model. When the model is trained, it only needs to introduce other task models sharing …