5 citations · 9 across the 3 of their papers we have counts for
3 papers
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…
Stay Tuned: An Empirical Study of the Impact of Hyperparameters on LLM Tuning in Real-World Applications
Alon Halfon, Shai Gretz, Ofir Arviv +6
Fine-tuning Large Language Models (LLMs) is an effective method to enhance their performance on downstream tasks. However, choosing the appropriate setting of tuning hyperparameter…
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…