mlsanityData to 7 Oct 2026

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

arXiv 2312.16171 ↗First posted 26 Dec 2023cs.CL cs.AIcited by 48

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Abstract (arXiv)

This paper introduces 26 guiding principles designed to streamline the process of querying and prompting large language models. Our goal is to simplify the underlying concepts of formulating questions for various scales of large language models, examining their abilities, and enhancing user comprehension on the behaviors of different scales of large language models when feeding into different prompts. Extensive experiments are conducted on LLaMA-1/2 (7B, 13B and 70B), GPT-3.5/4 to verify the effectiveness of the proposed principles on instructions and prompts design. We hope that this work can provide a better guide for researchers working on the prompting of large language models. Project page is available at https://github.com/VILA-Lab/ATLAS.

Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). Builds on 16 of its 23 references that are in the map. First posted on arXiv 26 Dec 2023.

Builds on

16 of 23 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  7. 2022Competition-Level Code Generation with AlphaCodecited by 1,427
  8. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  9. 2021Scaling Language Models: Methods, Analysis & Insights from Training Gophercited by 1,199
  10. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
  11. 2022Can language models learn from explanations in context?cited by 248
  12. 2023MathPrompter: Mathematical Reasoning using Large Language Modelscited by 236
4 more
  1. 2022Ask Me Anything: A simple strategy for prompting language modelscited by 155
  2. 2023Evaluating Open-Domain Question Answering in the Era of Large Language Modelscited by 110
  3. 2023Guiding Large Language Models via Directional Stimulus Promptingcited by 94
  4. 2023Plum: Prompt Learning using Metaheuristiccited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 28; 2025: 14; 2026: 6.

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  1. 2024The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performancecited by 97
  2. 2024The Benefits of a Concise Chain of Thought on Problem-Solving in Large Language Modelscited by 62
  3. 2024CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferencescited by 56
  4. 2024Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Modelscited by 45
  5. 2024Self-Reflection in LLM Agents: Effects on Problem-Solving Performancecited by 38
  6. 2024CUTE: Measuring LLMs' Understanding of Their Tokenscited by 28
  7. 2024What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Usecited by 24
  8. 2024Materials science in the era of large language models: a perspectivecited by 23
  9. 2024Scalable Qualitative Coding with LLMs: Chain-of-Thought Reasoning Matches Human Performance in Some Hermeneutic Taskscited by 22
  10. 2024Perception of Knowledge Boundary for Large Language Models through Semi-open-ended Question Answeringcited by 20
  11. 2024Themis: A Reference-free NLG Evaluation Language Model with Flexibility and Interpretabilitycited by 19
  12. 2024PHAnToM: Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language Modelscited by 16
36 more
  1. 2024LangGPT: Rethinking Structured Reusable Prompt Design Framework for LLMs from the Programming Languagecited by 12
  2. 2024Uncertainty Quantification in Large Language Models Through Convex Hull Analysiscited by 12
  3. 2024Towards Hierarchical Multi-Agent Workflows for Zero-Shot Prompt Optimizationcited by 10
  4. 2025GAAPO: Genetic Algorithmic Applied to Prompt Optimizationcited by 10
  5. 2024An Empirical Study of In-context Learning in LLMs for Machine Translationcited by 9
  6. 2024LLM Based Multi-Agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domaincited by 9
  7. 2024RS-GPT4V: A Unified Multimodal Instruction-Following Dataset for Remote Sensing Image Understandingcited by 9
  8. 2024Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generationcited by 7
  9. 2025Bandit-Based Prompt Design Strategy Selection Improves Prompt Optimizerscited by 7
  10. 2025LLM Sensitivity Evaluation Framework for Clinical Diagnosiscited by 7
  11. 2024Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Predictioncited by 6
  12. 2025What Makes a Good Natural Language Prompt?cited by 6
  13. 2025Understanding and Supporting Formal Email Exchange by Answering AI-Generated Questionscited by 5
  14. 2024What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Modelscited by 4
  15. 2024Minstrel: Structural Prompt Generation with Multi-Agents Coordination for Non-AI Expertscited by 4
  16. 2025Online Learning Defense against Iterative Jailbreak Attacks via Prompt Optimizationcited by 3
  17. 2026An Agentic Approach to Generating XAI-Narrativescited by 3
  18. 2024Enhancing Explainability in Multimodal Large Language Models Using Ontological Contextcited by 2
  19. 2025Identifying Helpful Context for LLM-based Vulnerability Repair: A Preliminary Studycited by 2
  20. 2025Prompting Test-Time Scaling Is A Strong LLM Reasoning Data Augmentationcited by 2
  21. 2024BERT-Enhanced Retrieval Tool for Homework Plagiarism Detection Systemcited by 1
  22. 2024PyGen: A Collaborative Human-AI Approach to Python Package Creationcited by 1
  23. 2025Rethinking Prompt Optimizers: From Prompt Merits to Optimizationcited by 1
  24. 2025RELRaE: LLM-Based Relationship Extraction, Labelling, Refinement, and Evaluationcited by 1
  25. 2025Decentralized Multi-Agent Goal Assignment for Path Planning using Large Language Modelscited by 1
  26. 2026When Preferences Fail to Become Incentives: A Utility-Behavior Gap in Large Language Modelscited by 1
  27. 2024Searching Realistic-Looking Adversarial Objects For Autonomous Driving Systemscited by 0
  28. 2024Creating a Gen-AI based Track and Trace Assistant MVP (SuperTracy) for PostNLcited by 0
  29. 2024Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generationcited by 0
  30. 2025SUMART: SUMmARizing Translation from Wordy to Concise Expressioncited by 0
  31. 2025A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentencescited by 0
  32. 2025Model selection meets clinical semantics: Optimizing ICD-10-CM prediction via LLM-as-Judge evaluation, redundancy-aware sampling, and section-aware fine-tuningcited by 0
  33. 2026OI-Bench: An Option Injection Benchmark for Evaluating LLM Susceptibility to Directive Interferencecited by 0
  34. 2026Evaluating Prompt Engineering Strategies for Sentiment Control in AI-Generated Textscited by 0
  35. 2026PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responsescited by 0
  36. 2026Do Influence Tactics Matter? Investigating Prompt Framing Effects in LLM Code Generationcited by 0