:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Doyle, Colin
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language
Online Access:	https://arxiv.org/abs/2411.05778
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks
by: Vatsal, Shubham, et al.
Published: (2024)

Detection Method for Prompt Injection by Integrating Pre-trained Model and Heuristic Feature Engineering
by: Ji, Yi, et al.
Published: (2025)

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure
by: Cook, David A.
Published: (2026)

When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs
by: Seleznyov, Mikhail, et al.
Published: (2025)

Using LLMs for Automated Privacy Policy Analysis: Prompt Engineering, Fine-Tuning and Explainability
by: Chen, Yuxin, et al.
Published: (2025)

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques
by: Schulhoff, Sander, et al.
Published: (2024)

Prompt Engineering a Prompt Engineer
by: Ye, Qinyuan, et al.
Published: (2023)

A Survey on Prompting Techniques in LLMs
by: Bhandari, Prabin
Published: (2023)

Your Absorbing Discrete Diffusion Secretly Models the Bayesian Posterior
by: Doyle, Cooper
Published: (2025)

LLMs as Strategic Actors: Behavioral Alignment, Risk Calibration, and Argumentation Framing in Geopolitical Simulations
by: Solopova, Veronika, et al.
Published: (2026)

Prompting Science Report 1: Prompt Engineering is Complicated and Contingent
by: Meincke, Lennart, et al.
Published: (2025)

The Future of MLLM Prompting is Adaptive: A Comprehensive Experimental Evaluation of Prompt Engineering Methods for Robust Multimodal Performance
by: Mohanty, Anwesha, et al.
Published: (2025)

Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey
by: Li, Haochen, et al.
Published: (2024)

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs
by: Naderi, Nariman, et al.
Published: (2025)

Autonomous Prompt Engineering in Large Language Models
by: Kepel, Daan, et al.
Published: (2024)

Integrating Chemistry Knowledge in Large Language Models via Prompt Engineering
by: Liu, Hongxuan, et al.
Published: (2024)

Reflexive Prompt Engineering: A Framework for Responsible Prompt Engineering and Interaction Design
by: Djeffal, Christian
Published: (2025)

Natural Language Declarative Prompting (NLD-P): A Modular Governance Method for Prompt Design Under Model Drift
by: Kim, Hyunwoo, et al.
Published: (2026)

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
by: Guo, Qingyan, et al.
Published: (2023)

PromptTailor: Multi-turn Intent-Aligned Prompt Synthesis for Lightweight LLMs
by: Xu, Yizhou, et al.
Published: (2025)

SynthesizeMe! Inducing Persona-Guided Prompts for Personalized Reward Models in LLMs
by: Ryan, Michael J, et al.
Published: (2025)

Prior Prompt Engineering for Reinforcement Fine-Tuning
by: Taveekitworachai, Pittawat, et al.
Published: (2025)

Automatic Prompt Engineering with No Task Cues and No Tuning
by: Chowdhury, Faisal, et al.
Published: (2026)

RePrompt: Planning by Automatic Prompt Engineering for Large Language Models Agents
by: Chen, Weizhe, et al.
Published: (2024)

Triggering Hallucinations in LLMs: A Quantitative Study of Prompt-Induced Hallucination in Large Language Models
by: Sato, Makoto
Published: (2025)

Enhancing Decision-Making of Large Language Models via Actor-Critic
by: Dong, Heng, et al.
Published: (2025)

Exploring Prompt Engineering: A Systematic Review with SWOT Analysis
by: Singh, Aditi, et al.
Published: (2024)

Fine-tuned Large Language Models (LLMs): Improved Prompt Injection Attacks Detection
by: Rahman, Md Abdur, et al.
Published: (2024)

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
by: Hong, Junyuan, et al.
Published: (2023)

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques
by: Aly, Walid Mohamed, et al.
Published: (2025)

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
by: Ning, Xuefei, et al.
Published: (2023)

Testing the Effect of Code Documentation on Large Language Model Code Understanding
by: Macke, William, et al.
Published: (2024)

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
by: Sahoo, Pranab, et al.
Published: (2024)

SouLLMate: An Application Enhancing Diverse Mental Health Support with Adaptive LLMs, Prompt Engineering, and RAG Techniques
by: Guo, Qiming, et al.
Published: (2024)

Intelligent Understanding of Large Language Models in Traditional Chinese Medicine Based on Prompt Engineering Framework
by: Chen, Yirui, et al.
Published: (2024)

Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement
by: Zhan, Pengwei, et al.
Published: (2024)

GRAD-SUM: Leveraging Gradient Summarization for Optimal Prompt Engineering
by: Austin, Derek, et al.
Published: (2024)

You Don't Need Prompt Engineering Anymore: The Prompting Inversion
by: Khan, Imran
Published: (2025)

Asymmetric Actor-Critic for Multi-turn LLM Agents
by: Jiang, Shuli, et al.
Published: (2026)

Exploring Prompt-Based Methods for Zero-Shot Hypernym Prediction with Large Language Models
by: Tikhomirov, Mikhail, et al.
Published: (2024)