4 citations · 12 across the 7 of their papers we have counts for
13 papers · 1 filter
Dual Reinforcement-Based Specification Generation for Image De-Rendering
Ramakanth Pasunuru, David Rosenberg, Gideon Mann +1
Advances in deep learning have led to promising progress in inferring graphics programs by de-rendering computer-generated images. However, current methods do not explore which dec…
Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley +4
The progress in Query-focused Multi-Document Summarization (QMDS) has been limited by the lack of sufficient largescale high-quality training datasets. We present two QMDS training…
DORB: Dynamically Optimizing Multiple Rewards with Bandits
Ramakanth Pasunuru, Han Guo, Mohit Bansal
Policy gradients-based reinforcement learning has proven to be a promising approach for directly optimizing non-differentiable evaluation metrics for language generation tasks. How…
Evaluating Interactive Summarization: an Expansion-Based Framework
Ori Shapira, Ramakanth Pasunuru, Hadar Ronen +3
Allowing users to interact with multi-document summarizers is a promising direction towards improving and customizing summary results. Different ideas for interactive summarization…
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits
Han Guo, Ramakanth Pasunuru, Mohit Bansal
Domain adaptation performance of a learning algorithm on a target domain is a function of its source domain error and a divergence measure between the data distribution of these tw…
Continual and Multi-Task Architecture Search
Ramakanth Pasunuru, Mohit Bansal
Architecture search is the process of automatically learning the neural model or cell structure that best suits the given task. Recently, this approach has shown promising performa…