2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CL2024★ 5 cited
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…
cs.LG2024★ 3 cited
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…
cs.CL2022★ 2 cited
Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours
Eyal Shnarch, Alon Halfon, Ariel Gera +19
Text classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a custom classifier typically requires coding skills and ML kn…