output
20022025
most citedGW190814: Gravitational Waves from the Coalescence of a 23 M Black Hole with a 2.6 M Compact Object

1.8k citations

Showing 2019 · cs.CLShow all

7 papers · 2 filters

cs.CL20194 cited

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…

cs.CL20198 cited

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…

cs.CL201915 cited

Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation

Amit Moryossef, Yoav Goldberg, Ido Dagan

Data-to-text generation can be conceptually divided into two parts: ordering and structuring the information (planning), and generating fluent language describing the information (…

cs.CL2019

Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion

Jonathan Mamou, Oren Pereg, Moshe Wasserblat +1

In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set…

cs.CL201910 cited

Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages

Shauli Ravfogel, Yoav Goldberg, Tal Linzen

How do typological properties such as word order and morphological case marking affect the ability of neural sequence models to acquire the syntax of a language? Cross-linguistic c…

cs.CL20193 cited

ABI Neural Ensemble Model for Gender Prediction Adapt Bar-Ilan Submission for the CLIN29 Shared Task on Gender Prediction

Eva Vanmassenhove, Amit Moryossef, Alberto Poncelas +2

We present our system for the CLIN29 shared task on cross-genre gender detection for Dutch. We experimented with a multitude of neural models (CNN, RNN, LSTM, etc.), more "traditio…