172 citations · 646 across the 82 of their papers we have counts for
10 papers · 1 filter
Controlled Crowdsourcing for High-Quality QA-SRL Annotation
Paul Roit, Ayal Klein, Daniela Stepanov +5
Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an attractive open and natural flavour of SRL, potentially attainable from laymen. Recently, a large-scale cr…
Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets
Ohad Rozen, Vered Shwartz, Roee Aharoni +1
Phenomenon-specific "adversarial" datasets have been recently designed to perform targeted stress-tests for particular inference types. Recent work (Liu et al., 2019a) proposed tha…
Improving Quality and Efficiency in Plan-based Neural Data-to-Text Generation
Amit Moryossef, Ido Dagan, Yoav Goldberg
We follow the step-by-step approach to neural data-to-text generation we proposed in Moryossef et al (2019), in which the generation process is divided into a text-planning stage f…
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System
Oren Pereg, Daniel Korat, Moshe Wasserblat +2
We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction. The system is interpretable and user friendly and does not require labeled training da…
Better Rewards Yield Better Summaries: Learning to Summarise Without References
Florian Böhm, Yang Gao, Christian M. Meyer +3
Reinforcement Learning (RL) based document summarisation systems yield state-of-the-art performance in terms of ROUGE scores, because they directly use ROUGE as the rewards during…
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution
Shany Barhom, Vered Shwartz, Alon Eirew +3
Recognizing coreferring events and entities across multiple texts is crucial for many NLP applications. Despite the task's importance, research focus was given mostly to within-doc…