mlsanityData to 14 Oct 2026

A Practical Survey on Zero-shot Prompt Design for In-context Learning

arXiv 2309.13205 ↗First posted 22 Sep 2023cs.CL cs.AI cs.ETcited by 49

Not on the map. Why?

Abstract (arXiv)

The remarkable advancements in large language models (LLMs) have brought about significant improvements in Natural Language Processing(NLP) tasks. This paper presents a comprehensive review of in-context learning techniques, focusing on different types of prompts, including discrete, continuous, few-shot, and zero-shot, and their impact on LLM performance. We explore various approaches to prompt design, such as manual design, optimization algorithms, and evaluation methods, to optimize LLM performance across diverse tasks. Our review covers key research studies in prompt engineering, discussing their methodologies and contributions to the field. We also delve into the challenges faced in evaluating prompt performance, given the absence of a single "best" prompt and the importance of considering multiple metrics. In conclusion, the paper highlights the critical role of prompt design in harnessing the full potential of LLMs and provides insights into the combination of manual design, optimization techniques, and rigorous evaluation for more effective and efficient use of LLMs in various NLP tasks.

Key facts. Cited by 49 papers in the map (data through 14 Oct 2026). Builds on 23 of its 31 references that are in the map. First posted on arXiv 22 Sep 2023.

Builds on

23 of 31 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  5. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  6. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  7. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  8. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  9. 2022Competition-Level Code Generation with AlphaCodecited by 1,462
  10. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,256
  11. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  12. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
11 more
  1. 2019How Can We Know What Language Models Know?cited by 959
  2. 2021GPT Understands, Toocited by 716
  3. 2021Learning To Retrieve Prompts for In-Context Learningcited by 648
  4. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 606
  5. 2022RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learningcited by 366
  6. 2020AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Promptscited by 249
  7. 2021Reframing Instructional Prompts to GPTk's Languagecited by 176
  8. 2022GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Modelscited by 127
  9. 2022Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Againcited by 83
  10. 2021BERTese: Learning to Speak to BERTcited by 82
  11. 2022Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too?cited by 49

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 16; 2025: 21; 2026: 11.

49 papers.

Sort:

By area:

  1. 2024Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelscited by 477
  2. 2023Large Language Models in Finance: A Surveycited by 226
  3. 2024Large Language Model Agent in Financial Trading: A Surveycited by 60
  4. 2025Knowledge Graph-Guided Retrieval Augmented Generationcited by 58
  5. 2024Visual Prompting in Multimodal Large Language Models: A Surveycited by 54
  6. 2024Large Language Model Agent as a Mechanical Designercited by 21
  7. 2024Fine-Tuning Vision-Language Model for Automated Engineering Drawing Information Extractioncited by 18
  8. 2024RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Informationcited by 14
  9. 2024LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Surveycited by 12
  10. 2024Data Generation Using Large Language Models for Text Classification: An Empirical Case Studycited by 11
  11. 2024Which Demographics do LLMs Default to During Annotation?cited by 10
  12. 2025Privacy-Aware RAG: Secure and Isolated Knowledge Retrievalcited by 10
37 more
  1. 2024OmniArch: Building Foundation Model For Scientific Computingcited by 9
  2. 2025AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveyscited by 8
  3. 2025LLM-Net: Democratizing LLMs-as-a-Service through Blockchain-based Expert Networkscited by 7
  4. 2025CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agentscited by 7
  5. 2026Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Futurecited by 6
  6. 2025Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understandingcited by 5
  7. 2025Efficient Model Selection for Time Series Forecasting via LLMscited by 4
  8. 2025Are All Prompt Components Value-Neutral? Understanding the Heterogeneous Adversarial Robustness of Dissected Prompt in Large Language Modelscited by 3
  9. 2025Sophia: A Persistent Agent Framework of Artificial Lifecited by 3
  10. 2024Leveraging Zero-Shot Prompting for Efficient Language Model Distillationcited by 2
  11. 2025PAFT: Prompt-Agnostic Fine-Tuningcited by 2
  12. 2025Integrating Personality into Digital Humans: A Review of LLM-Driven Approaches for Virtual Realitycited by 2
  13. 2025Conversational Process Model Redesigncited by 2
  14. 2025Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivitycited by 2
  15. 2025Large Language Models for Oral History Understanding with Text Classification and Sentiment Analysiscited by 2
  16. 2025Is General-Purpose AI Reasoning Sensitive to Data-Induced Cognitive Biases? Dynamic Benchmarking on Typical Software Engineering Dilemmascited by 2
  17. 2024Relay Decoding: Concatenating Large Language Models for Machine Translationcited by 1
  18. 2024ViDAS: Vision-based Danger Assessment and Scoringcited by 1
  19. 2024VERITAS-NLI : Validation and Extraction of Reliable Information Through Automated Scraping and Natural Language Inferencecited by 1
  20. 2025Multilingual LLMs Are Not Multilingual Thinkers: Evidence from Hindi Analogy Evaluationcited by 1
  21. 2025Mathematics with large language models as provers and verifierscited by 1
  22. 2025Using Large Language Models for Abstraction of Planning Domains - Extended Versioncited by 1
  23. 2025SVBRD-LLM: Self-Verifying Behavioral Rule Discovery for Autonomous Vehicle Identificationcited by 1
  24. 2026NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutionscited by 1
  25. 2024ClaimBrush: A Novel Framework for Automated Patent Claim Refinement Based on Large Language Modelscited by 0
  26. 2024VARS: Vision-based Assessment of Risk in Security Systemscited by 0
  27. 2025KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Frameworkcited by 0
  28. 2025Evaluation of the Automated Labeling Method for Taxonomic Nomenclature Through Prompt-Optimized Large Language Modelcited by 0
  29. 2026Time-Continuous Modeling for Temporal Affective Pattern Recognition in LLMscited by 0
  30. 2026Large Language Models for Math Education in Low-Resource Languages: A Study in Sinhala and Tamilcited by 0
  31. 2026Personalized Prediction of Perceived Message Effectiveness Using Large Language Model Based Digital Twinscited by 0
  32. 2026Retcon -- a Prompt-Based Technique for Precise Control of LLMs in Conversationscited by 0
  33. 2026UtilityMax Prompting: A Formal Framework for Multi-Objective Large Language Model Taskscited by 0
  34. 2026The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behaviorcited by 0
  35. 2026Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Studycited by 0
  36. 2026Evaluating Structured Information Extraction with Open Models in a High Risk Public Sector Applicationcited by 0
  37. 2026Large Models for Battery Prognostics and Health Management: A Review and Future Roadmapcited by 0