13 citations · 23 across the 7 of their papers we have counts for
6 papers · 1 filter
Conversational Prompt Engineering
Liat Ein-Dor, Orith Toledo-Ronen, Artem Spector +5
Prompts are how humans communicate with LLMs. Informative prompts are essential for guiding LLMs to produce the desired output. However, prompt engineering is often tedious and tim…
Fortunately, Discourse Markers Can Enhance Language Models for Sentiment Analysis
Liat Ein-Dor, Ilya Shnayderman, Artem Spector +3
In recent years, pretrained language models have revolutionized the NLP world, while achieving state of the art performance in various downstream tasks. However, in many cases, the…
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews
Matan Orbach, Orith Toledo-Ronen, Artem Spector +3
Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets. Such an evaluation is limited, and may not reflect t…
Multilingual Argument Mining: Datasets and Analysis
Orith Toledo-Ronen, Matan Orbach, Yonatan Bilu +2
The growing interest in argument mining and computational argumentation brings with it a plethora of Natural Language Understanding (NLU) tasks and corresponding datasets. However,…
Fast End-to-End Wikification
Ilya Shnayderman, Liat Ein-Dor, Yosi Mass +7
Wikification of large corpora is beneficial for various NLP applications. Existing methods focus on quality performance rather than run-time, and are therefore non-feasible for lar…
Learning Concept Abstractness Using Weak Supervision
Ella Rabinovich, Benjamin Sznajder, Artem Spector +4
We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data. Exploiting only minimal lingu…