SOTAVerified

Prompt Engineering

Prompt engineering is the process of designing and refining the prompts used to generate text from language models, such as GPT-3 or similar models. The goal of prompt engineering is to improve the quality and relevance of the generated text by carefully crafting the prompts to elicit the desired responses from the model.

Prompt engineering involves several steps, including selecting the appropriate model architecture and parameters, designing the prompt format and structure, selecting the appropriate task and training data, and fine-tuning the model using the selected prompt and data.

Prompt engineering is a crucial step in the development of language models, as it can greatly influence the quality and effectiveness of the model's responses. By carefully designing and refining the prompts used to generate text, researchers and developers can improve the accuracy and relevance of the model's output, making it more useful for a wide range of applications, including chatbots, language translation, content creation, and more.

Papers

Showing 801850 of 1236 papers

TitleStatusHype
Achieving Tool Calling Functionality in LLMs Using Only Prompt Engineering Without Fine-Tuning0
A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context0
Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Models0
AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework0
Adaptive Deep Reasoning: Triggering Deep Thinking When Needed0
Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection0
Addressing single object tracking in satellite imagery through prompt-engineered solutions0
ADO: Automatic Data Optimization for Inputs in LLM Prompts0
Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies0
Adversarial Text Purification: A Large Language Model Approach for Defense0
Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective0
A Foundation Model for Cell Segmentation0
A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts0
A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering0
A Framework for Ranking Content Providers Using Prompt Engineering and Self-Attention Network0
AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents0
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges0
AI-Copilot for Business Optimisation: A Framework and A Case Study in Production Scheduling0
AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning0
AI-Driven Virtual Teacher for Enhanced Educational Efficiency: Leveraging Large Pretrain Models for Autonomous Error Analysis and Correction0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation0
AI/ML Based Detection and Categorization of Covert Communication in IPv6 Network0
AI on AI: Exploring the Utility of GPT as an Expert Annotator of AI Publications0
A Large Language Model Pipeline for Breast Cancer Oncology0
FRANC: A Lightweight Framework for High-Quality Code Generation0
A Looming Replication Crisis in Evaluating Behavior in Language Models? Evidence and Solutions0
A Lost Opportunity for Vision-Language Models: A Comparative Study of Online Test-Time Adaptation for Vision-Language Models0
Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment0
A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models0
A Measure Based Generalizable Approach to Understandability0
A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI0
AMPO: Automatic Multi-Branched Prompt Optimization0
Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot0
An Empirical Categorization of Prompting Techniques for Large Language Models: A Practitioner's Guide0
An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing0
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models0
An Empirical Study of OpenAI API Discussions on Stack Overflow0
A New Type of Foundation Model Based on Recordings of People's Emotions and Physiology0
An Exploration of Higher Education Course Evaluation by Large Language Models0
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels0
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels0
An Initial Exploration of Default Images in Text-to-Image Generation0
AnnotatedTables: A Large Tabular Dataset with Language Model Annotations0
Antelope: Potent and Concealed Jailbreak Attack Strategy0
AoP-SAM: Automation of Prompts for Efficient Segmentation0
A Pedestrian is Worth One Prompt: Towards Language Guidance Person Re-Identification0
APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking0
A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean77.62Unverified
2Customized EnsembleHarmonic mean75.49Unverified
3MMRLHarmonic mean74.45Unverified
4MMRL++Harmonic mean74.44Unverified
5CoPromptHarmonic mean74.33Unverified
6HPT++Harmonic mean74.24Unverified
7HPTHarmonic mean74.17Unverified
8ProMetaRHarmonic mean74.09Unverified
9MetaPromptHarmonic mean74.02Unverified
10DePTHarmonic mean74.02Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean97.77Unverified
2HPT++Harmonic mean96.96Unverified
3MMRL++Harmonic mean96.75Unverified
4MMRLHarmonic mean96.68Unverified
5HPTHarmonic mean96.65Unverified
6CoPromptHarmonic mean96.55Unverified
7MetaPromptHarmonic mean96.32Unverified
8DePTHarmonic mean96.28Unverified
9ProMetaRHarmonic mean96.16Unverified
10RPOHarmonic mean96.03Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean77.94Unverified
2MMRL++Harmonic mean74.46Unverified
3HPT++Harmonic mean74.23Unverified
4MMRLHarmonic mean73.82Unverified
5CoPromptHarmonic mean72.79Unverified
6ProMetaRHarmonic mean72.31Unverified
7HPTHarmonic mean72.16Unverified
8PromptSRCHarmonic mean71.75Unverified
9DePTHarmonic mean71.09Unverified
10RPOHarmonic mean68.61Unverified
#ModelMetricClaimedVerifiedStatus
1MMRL++Harmonic mean91.94Unverified
2PromptKDHarmonic mean89.14Unverified
3HPT++Harmonic mean87.36Unverified
4MMRLHarmonic mean87.21Unverified
5CoPromptHarmonic mean85.84Unverified
6ProMetaRHarmonic mean85.3Unverified
7DePTHarmonic mean84.88Unverified
8HPTHarmonic mean84.82Unverified
9MetaPromptHarmonic mean83.38Unverified
10MaPLeHarmonic mean82.35Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean45.17Unverified
2MMRL++Harmonic mean42.24Unverified
3HPT++Harmonic mean41.33Unverified
4MMRLHarmonic mean41.15Unverified
5DePTHarmonic mean40.73Unverified
6HPTHarmonic mean40.28Unverified
7ProMetaRHarmonic mean40.25Unverified
8PromptSRCHarmonic mean40.15Unverified
9CoPromptHarmonic mean39.76Unverified
10MetaPromptHarmonic mean38.24Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean90.24Unverified
2HPTHarmonic mean87.16Unverified
3MMRL++Harmonic mean87.01Unverified
4MMRLHarmonic mean86.78Unverified
5ProMetaRHarmonic mean86.7Unverified
6DePTHarmonic mean86.46Unverified
7PromptSRCHarmonic mean85.95Unverified
8HPT++Harmonic mean85.85Unverified
9CoPromptHarmonic mean85.71Unverified
10MetaPromptHarmonic mean84.52Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean97.15Unverified
2HPT++Harmonic mean96.91Unverified
3CoPromptHarmonic mean96.87Unverified
4MMRLHarmonic mean96.74Unverified
5HPTHarmonic mean96.71Unverified
6MaPLeHarmonic mean96.58Unverified
7MMRL++Harmonic mean96.51Unverified
8ProMetaRHarmonic mean96.49Unverified
9CoCoOpHarmonic mean96.43Unverified
10DePTHarmonic mean96.37Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean83.13Unverified
2MMRL++Harmonic mean78.18Unverified
3MMRLHarmonic mean78.06Unverified
4DePTHarmonic mean77.79Unverified
5ProMetaRHarmonic mean76.72Unverified
6PromptSRCHarmonic mean76.58Unverified
7CoPromptHarmonic mean75.66Unverified
8HPT++Harmonic mean75.59Unverified
9HPTHarmonic mean75.57Unverified
10MetaPromptHarmonic mean75.48Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean82.6Unverified
2CoPromptHarmonic mean81.31Unverified
3MMRL++Harmonic mean81.28Unverified
4MMRLHarmonic mean81.2Unverified
5HPT++Harmonic mean81.11Unverified
6DePTHarmonic mean81.06Unverified
7HPTHarmonic mean80.88Unverified
8ProMetaRHarmonic mean80.82Unverified
9MetaPromptHarmonic mean80.62Unverified
10PromptSRCHarmonic mean80.52Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean86.1Unverified
2MMRLHarmonic mean83.89Unverified
3HPT++Harmonic mean83.81Unverified
4MMRL++Harmonic mean83.81Unverified
5ProMetaRHarmonic mean83.25Unverified
6HPTHarmonic mean83.16Unverified
7CoPromptHarmonic mean83.07Unverified
8PromptSRCHarmonic mean82.74Unverified
9DePTHarmonic mean82.46Unverified
10MetaPromptHarmonic mean81.35Unverified
#ModelMetricClaimedVerifiedStatus
1PromptKDHarmonic mean93.05Unverified
2CoPromptHarmonic mean91.4Unverified
3MaPLeHarmonic mean91.38Unverified
4ProMetaRHarmonic mean91.34Unverified
5MetaPromptHarmonic mean91.29Unverified
6DePTHarmonic mean91.22Unverified
7PromptSRCHarmonic mean91.1Unverified
8MMRL++Harmonic mean91.1Unverified
9HPT++Harmonic mean91.09Unverified
10MMRLHarmonic mean91.03Unverified
#ModelMetricClaimedVerifiedStatus
1POMPTop-1 accuracy %51.6Unverified
2MMRLTop-1 accuracy %51.2Unverified
3HPT++Top-1 accuracy %51.18Unverified
4PromptSRCTop-1 accuracy %50.9Unverified
5MaPLeTop-1 accuracy %50.9Unverified
6HPTTop-1 accuracy %50.85Unverified
7CoCoOpTop-1 accuracy %50.63Unverified
8CoPromptTop-1 accuracy %50.5Unverified
9CLIPTop-1 accuracy %47.77Unverified
#ModelMetricClaimedVerifiedStatus
1POMPTop-1 accuracy %77.9Unverified
2PromptSRCTop-1 accuracy %77.8Unverified
3MMRLTop-1 accuracy %77.53Unverified
4HPT++Top-1 accuracy %77.52Unverified
5CoPromptTop-1 accuracy %77.51Unverified
6HPTTop-1 accuracy %77.38Unverified
7MaPLeTop-1 accuracy %76.98Unverified
8CoCoOPTop-1 accuracy %76.18Unverified
9CLIPTop-1 accuracy %73.96Unverified
#ModelMetricClaimedVerifiedStatus
1POMPTop-1 accuracy %49.8Unverified
2PromptSRCTop-1 accuracy %49.55Unverified
3CoPromptTop-1 accuracy %49.43Unverified
4HPTTop-1 accuracy %49.36Unverified
5HPT++Top-1 accuracy %49.28Unverified
6MMRLTop-1 accuracy %49.17Unverified
7MaPLeTop-1 accuracy %49.15Unverified
8CoCoOpTop-1 accuracy %48.75Unverified
9CLIPTop-1 accuracy %46.15Unverified
#ModelMetricClaimedVerifiedStatus
1HPT++Top-1 accuracy %65.31Unverified
2HPTTop-1 accuracy %65.25Unverified
3MMRLTop-1 accuracy %64.47Unverified
4PromptSRCTop-1 accuracy %64.35Unverified
5CoCoOpTop-1 accuracy %64.07Unverified
6MaPLeTop-1 accuracy %64.07Unverified
7POMPTop-1 accuracy %63.8Unverified
8CLIPTop-1 accuracy %60.83Unverified
#ModelMetricClaimedVerifiedStatus
1POMPAccuracy25.3Unverified
2VPTAccuracy24.8Unverified