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 651700 of 1236 papers

TitleStatusHype
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature InterpretationCode1
Easy Problems That LLMs Get WrongCode2
Adaptive In-conversation Team Building for Language Model AgentsCode7
Can Graph Learning Improve Planning in LLM-based Agents?Code2
PromptWizard: Task-Aware Prompt Optimization FrameworkCode7
Automated Real-World Sustainability Data Generation from Images of Buildings0
ORLM: A Customizable Framework in Training Large Models for Automated Optimization ModelingCode3
WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence0
A Preliminary Empirical Study on Prompt-based Unsupervised Keyphrase Extraction0
Adapting PromptORE for Modern History: Information Extraction from Hispanic Monarchy Documents of the XVIth CenturyCode0
Optimizing Large Language Models for OpenAPI Code CompletionCode2
Detection and Positive Reconstruction of Cognitive Distortion sentences: Mandarin Dataset and Evaluation0
What Do You See? Enhancing Zero-Shot Image Classification with Multimodal Large Language ModelsCode0
A Lost Opportunity for Vision-Language Models: A Comparative Study of Online Test-Time Adaptation for Vision-Language Models0
Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces0
Investigating Persuasion Techniques in Arabic: An Empirical Study Leveraging Large Language Models0
Depth Prompting for Sensor-Agnostic Depth EstimationCode0
Improving face generation quality and prompt following with synthetic captions0
Revolutionizing Process Mining: A Novel Architecture for ChatGPT Integration and Enhanced User Experience through Optimized Prompt Engineering0
Realistic Evaluation of Toxicity in Large Language Models0
Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers0
When Large Language Models Meet Optical Networks: Paving the Way for Automation0
Automated Repair of AI Code with Large Language Models and Formal Verification0
Meaning-Typed Programming: Language Abstraction and Runtime for Model-Integrated Applications0
Exploring the Potential of Conversational AI Support for Agent-Based Social Simulation Model Design0
E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple PredictionCode0
Large Language Model in Financial Regulatory Interpretation0
Exploring the Capabilities of Large Multimodal Models on Dense TextCode4
Can We Use Large Language Models to Fill Relevance Judgment Holes?Code1
Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization0
Traj-LLM: A New Exploration for Empowering Trajectory Prediction with Pre-trained Large Language Models0
FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering0
Prompting Task Trees using Gemini: Methodologies and Insights0
CityLLaVA: Efficient Fine-Tuning for VLMs in City ScenarioCode2
Towards A Human-in-the-Loop LLM Approach to Collaborative Discourse AnalysisCode0
Exploring prompts to elicit memorization in masked language model-based named entity recognition0
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education0
MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering0
Mothman at SemEval-2024 Task 9: An Iterative System for Chain-of-Thought Prompt Optimization0
Aloe: A Family of Fine-tuned Open Healthcare LLMsCode1
Exploring the Capabilities of Large Language Models for Generating Diverse Design SolutionsCode0
Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices0
CACTUS: Chemistry Agent Connecting Tool-Usage to ScienceCode1
WIBA: What Is Being Argued? A Comprehensive Approach to Argument MiningCode0
Enhancing Surgical Robots with Embodied Intelligence for Autonomous Ultrasound Scanning0
UMass-BioNLP at MEDIQA-M3G 2024: DermPrompt -- A Systematic Exploration of Prompt Engineering with GPT-4V for Dermatological DiagnosisCode0
Probabilistic Inference in Language Models via Twisted Sequential Monte CarloCode1
Semantic Routing for Enhanced Performance of LLM-Assisted Intent-Based 5G Core Network Management and OrchestrationCode7
A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI0
PRISM: A Promptable and Robust Interactive Segmentation Model with Visual PromptsCode1
Show:102550
← PrevPage 14 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