146 citations · 646 across the 40 of their papers we have counts for
4 papers · 1 filter
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
Tian Shi, Yaser Keneshloo, Naren Ramakrishnan +1
In the past few years, neural abstractive text summarization with sequence-to-sequence (seq2seq) models have gained a lot of popularity. Many interesting techniques have been propo…
Deep Transfer Reinforcement Learning for Text Summarization
Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy
Deep neural networks are data hungry models and thus face difficulties when attempting to train on small text datasets. Transfer learning is a potential solution but their effectiv…
Deep Reinforcement Learning For Sequence to Sequence Models
Yaser Keneshloo, Tian Shi, Naren Ramakrishnan +1
In recent times, sequence-to-sequence (seq2seq) models have gained a lot of popularity and provide state-of-the-art performance in a wide variety of tasks such as machine translati…
DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks
Mahmudur Rahman, Tanay Kumar Saha, Mohammad Al Hasan +2
The temporal dynamics of a complex system such as a social network or a communication network can be studied by understanding the patterns of link appearance and disappearance over…