no code implementations • 12 Oct 2022 • Sharan Narasimhan, Pooja Shekar, Suvodip Dey, Maunendra Sankar Desarkar
Text Style Transfer (TST) is performable through approaches such as latent space disentanglement, cycle-consistency losses, prototype editing etc.
1 code implementation • NAACL 2022 • Sharan Narasimhan, Suvodip Dey, Maunendra Sankar Desarkar
We empirically show that this (a) produces a better organised latent space that clusters stylistically similar sentences together, (b) performs best on a diverse set of text style transfer tasks than similar denoising-inspired baselines, and (c) is capable of fine-grained control of Style Transfer strength.
2 code implementations • ACL 2020 • Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran
To make attention mechanisms more faithful and plausible, we propose a modified LSTM cell with a diversity-driven training objective that ensures that the hidden representations learned at different time steps are diverse.