4 citations · 12 across the 4 of their papers we have counts for
6 papers
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…
Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation
Ori Shapira, David Gabay, Yang Gao +5
Conducting a manual evaluation is considered an essential part of summary evaluation methodology. Traditionally, the Pyramid protocol, which exhaustively compares system summaries…
AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning
Han Guo, Ramakanth Pasunuru, Mohit Bansal
Multi-task learning (MTL) has achieved success over a wide range of problems, where the goal is to improve the performance of a primary task using a set of relevant auxiliary tasks…
Reinforced Video Captioning with Entailment Rewards
Ramakanth Pasunuru, Mohit Bansal
Sequence-to-sequence models have shown promising improvements on the temporal task of video captioning, but they optimize word-level cross-entropy loss during training. First, usin…