activity
20172019
most citedStory Generation from Sequence of Independent Short Descriptions

81 citations · 81 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG2019

OmniNet: A unified architecture for multi-modal multi-task learning

Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain

Transformer is a popularly used neural network architecture, especially for language understanding. We introduce an extended and unified architecture that can be used for tasks inv…

cs.CL2019

Unified Semantic Parsing with Weak Supervision

Priyanka Agrawal, Parag Jain, Ayushi Dalmia +3

Semantic parsing over multiple knowledge bases enables a parser to exploit structural similarities of programs across the multiple domains. However, the fundamental challenge lies…

cs.LG2018

On Controllable Sparse Alternatives to Softmax

Anirban Laha, Saneem A. Chemmengath, Priyanka Agrawal +3

Converting an n-dimensional vector to a probability distribution over n objects is a commonly used component in many machine learning tasks like multiclass classification, multilab…

cs.LG2018

Deep Domain Adaptation under Deep Label Scarcity

Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal +1

The goal behind Domain Adaptation (DA) is to leverage the labeled examples from a source domain so as to infer an accurate model in a target domain where labels are not available o…

cs.CL201781 cited

Story Generation from Sequence of Independent Short Descriptions

Parag Jain, Priyanka Agrawal, Abhijit Mishra +3

Existing Natural Language Generation (NLG) systems are weak AI systems and exhibit limited capabilities when language generation tasks demand higher levels of creativity, originali…