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 10511100 of 1236 papers

TitleStatusHype
Prompt Engineering a Prompt Engineer0
Indicative Summarization of Long DiscussionsCode0
Automating Governing Knowledge Commons and Contextual Integrity (GKC-CI) Privacy Policy Annotations with Large Language ModelsCode0
Efficient Black-Box Adversarial Attacks on Neural Text DetectorsCode0
Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias0
Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral AnalysisCode0
A Multi-Modal Foundation Model to Assist People with Blindness and Low Vision in Environmental Interaction0
From Chatbots to PhishBots? -- Preventing Phishing scams created using ChatGPT, Google Bard and Claude0
Prompt-Engineering and Transformer-based Question Generation and Evaluation0
Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset0
Better integrating vision and semantics for improving few-shot classificationCode0
Apollo: Zero-shot MultiModal Reasoning with Multiple ExpertsCode0
A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models0
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles0
Unleashing the potential of prompt engineering for large language models0
Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models0
TaskDiff: A Similarity Metric for Task-Oriented Conversations0
Prompt Engineering Through the Lens of Optimal Control0
Enhancing Zero-Shot Crypto Sentiment with Fine-tuned Language Model and Prompt Engineering0
Interactive Task Planning with Language Models0
Configuration Validation with Large Language Models0
Human-in-the-loop Machine Translation with Large Language ModelCode0
Multimodal Large Language Model for Visual Navigation0
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques0
LLMs Killed the Script Kiddie: How Agents Supported by Large Language Models Change the Landscape of Network Threat Testing0
Large Language Models for Propaganda DetectionCode0
Cost-Efficient Prompt Engineering for Unsupervised Entity Resolution0
LLM4VV: Developing LLM-Driven Testsuite for Compiler ValidationCode0
Understanding prompt engineering may not require rethinking generalization0
Investigating the Limitation of CLIP Models: The Worst-Performing Categories0
Co-audit: tools to help humans double-check AI-generated content0
SPELL: Semantic Prompt Evolution based on a LLM0
A Brief History of Prompt: Leveraging Language Models. (Through Advanced Prompting)0
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering0
A Sign Language Recognition System with Pepper, Lightweight-Transformer, and LLM0
Exploring Small Language Models with Prompt-Learning Paradigm for Efficient Domain-Specific Text Classification0
An AI Chatbot for Explaining Deep Reinforcement Learning Decisions of Service-oriented SystemsCode0
FaceGemma: Enhancing Image Captioning with Facial Attributes for Portrait Images0
A Chat About Boring Problems: Studying GPT-based text normalization0
A Practical Survey on Zero-shot Prompt Design for In-context Learning0
AI-Copilot for Business Optimisation: A Framework and A Case Study in Production Scheduling0
Is GPT4 a Good Trader?0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation0
PRE: Vision-Language Prompt Learning with Reparameterization EncoderCode0
An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing0
Unveiling the potential of large language models in generating semantic and cross-language clones0
Detecting Natural Language Biases with Prompt-based Learning0
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models0
Toward Reproducing Network Research Results Using Large Language Models0
Leveraging Large Language Models for Exploiting ASR Uncertainty0
Show:102550
← PrevPage 22 of 25Next →

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
7MMRL++Harmonic mean91.1Unverified
8PromptSRCHarmonic 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
4MaPLeTop-1 accuracy %50.9Unverified
5PromptSRCTop-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