Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 20
Papers
Note The paper itself does not give a one-size-fits-all answer. However, subsequent research and practical guides in the field of prompt engineering can offer some guidance: - Start Small and Test: It is common to start with a small number of examples, typically between 2 to 5 shots . The first example often provides the most significant performance boost . - Diminishing Returns: Performance typically improves up to a certain point and then plateaus - deepseek:0c716819-dc61-4086-bf9c-497bc92c37fb
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Large Language Models Are Human-Level Prompt Engineers
Paper • 2211.01910 • Published • 1 -
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 44 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3 -
Large Language Models Understand and Can be Enhanced by Emotional Stimuli
Paper • 2307.11760 • Published • 1 -
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training
Paper • 2411.15124 • Published • 68 -
Attention Is All You Need
Paper • 1706.03762 • Published • 129 -
The Prompt Report: A Systematic Survey of Prompting Techniques
Paper • 2406.06608 • Published • 68 -
The Llama 3 Herd of Models
Paper • 2407.21783 • Published • 119