How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs
cs.SE, cs.AI, cs.HC
Submitted: 2026-09-28
Updated: 2026-09-28
Sources
- DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
- Tailored-LLaMA: Optimizing Few-Shot Learning in Pruned LLaMA Models with Task-Specific Prompts
- Selective Annotation Makes Language Models Better Few-Shot Learners
- Self-Consistency Improves Chain of Thought Reasoning in Language Models
- Non-Determinism of "Deterministic" LLM Settings
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