Definition: In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.
Input: Pre-trained word embeddings are the primary
method for transfer learning in several Natural Language Processing (NLP) tasks. Recent
works have focused on using unsupervised
techniques such as language modeling to obtain these embeddings. In contrast, this work
focuses on extracting representations from
multiple pre-trained supervised models, which
enriches word embeddings with task and domain specific knowledge. Experiments performed in cross-task, cross-domain and crosslingual settings indicate that such supervised
embeddings are helpful, especially in the lowresource setting, but the extent of gains is dependent on the nature of the task and domain.
Output:
extract contextual embeddings from off-the-shelf supervised model. Helps downstream NLP models in low-resource settings