prompt chunking, generative models
Split long prompts.
758 technical terms and definitions
Split long prompts.
Combine multiple prompts.
Prompt compression reduces token count while preserving information to fit context limits.
Vector representation of prompts.
Sophisticated techniques for crafting effective prompts.
Craft prompts for grounded generation.
Prompt engineering crafts input text to elicit desired behaviors from language models.
Combine predictions from multiple prompts.
Adversarial inputs to subvert model.
Techniques to prevent injection.
Defend against prompt injection: separate system/user prompts, filter inputs, use structured output, limit tool access.
Prompt injection inserts malicious instructions into prompts attempting to hijack model behavior.
Attack where user input tricks model into ignoring instructions or leaking info.
Trick model into revealing system prompts or instructions.
I can help you build a reusable prompt library with templates, variables, and patterns for consistent high-quality outputs.
Prompt mining discovers effective prompts by searching large candidate spaces.
Check prompts before processing.
Prompt optimization systematically improves prompts to maximize task performance.
Automatically improve prompts through search or gradient-based methods.
Prompt sensitivity measures performance variation across phrasings and formats.
How to format effective prompts.
Prompt templates define reusable patterns for consistent task formatting.
Reusable prompt structures.
Cut off excess tokens.
Prompt tuning learns continuous prompt embeddings through gradient descent.
Learn soft prompts (continuous vectors) while keeping the model frozen.
Version control prompts like code. Track changes, A/B test versions, rollback if quality drops.
Emphasize prompt parts differently.
Assign different importance to different parts of the prompt.
Use prompts to separate tasks.
Edit images by modifying text prompts.
Prompt-to-prompt editing modifies images by adjusting text prompts while preserving structure.
Prompt = text you feed the model. Clear role, task, input format, and constraints = more reliable and controllable outputs.
Segment using various prompt types.
Promptfoo tests prompts and models. CLI tool. Compare outputs.
PromptLayer logs and versions prompts. Track changes, A/B test.
Resolve pronouns to antecedents.
Create mathematical proofs.
Propensity scores weight training examples by inverse probability of exposure to debias recommendation models.
Infer properties of training data.
Generate property tests.
Test general properties rather than examples.
Prophet is an additive time series model decomposing signals into trend seasonality and holiday components with automatic changepoint detection.
Sample by dataset size.
AI drafts business proposals. Structure, persuasion.
Retrieve atomic facts/propositions instead of passages.
Proprietary models have restricted access to weights and implementation.
Identify sensitive medical data.
Protective capacity maintains deliberate excess at non-constraints enabling system flexibility.
Design proteins with desired properties.