most citedUnsupervised Neural Stylistic Text Generation using Transfer learning and Adapters

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20221 cited

Unsupervised Neural Stylistic Text Generation using Transfer learning and Adapters

Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah, Dan Roth

Research has shown that personality is a key driver to improve engagement and user experience in conversational systems. Conversational agents should also maintain a consistent per…

cs.CV2019

Monitoring of people entering and exiting private areas using Computer Vision

Vinay Kumar, P Nagabhushan

Entry-Exit surveillance is a novel research problem that addresses security concerns when people attain absolute privacy in camera forbidden areas such as toilets and changing room…

cs.CV2019

Appearance invariant Entry-Exit matching using visual soft biometric traits

Vinay Kumar, P Nagabhushan

The problem of appearance invariant subject recognition for Entry-Exit surveillance applications is addressed. A novel Semantic Entry-Exit matching model that makes use of ancillar…

cs.CL2019

Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations

Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary +3

This paper presents the submissions by Team Dr.Quad to the ACL-BioNLP 2019 shared task on Textual Inference and Question Entailment in the Medical Domain. Our system is based on th…

cs.LG2019

WriterForcing: Generating more interesting story endings

Prakhar Gupta, Vinayshekhar Bannihatti Kumar, Mukul Bhutani +1

We study the problem of generating interesting endings for stories. Neural generative models have shown promising results for various text generation problems. Sequence to Sequence…