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Automatic Prompt Engineering with No Task Cues and No Tuning

arXiv 2601.03130 ↗First posted 6 Jan 2026cs.AI cs.CLcited by 0

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Abstract (arXiv)

This paper presents a system for automatic prompt engineering that is much simpler in both design and application and yet as effective as the existing approaches. It requires no tuning and no explicit clues about the task. We evaluated our approach on cryptic column name expansion (CNE) in database tables, a task which is critical for tabular data search, access, and understanding and yet there has been very little existing work. We evaluated on datasets in two languages, English and German. This is the first work to report on the application of automatic prompt engineering for the CNE task. To the best of our knowledge, this is also the first work on the application of automatic prompt engineering for a language other than English.

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References · 17

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  3. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
  4. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
  5. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 832
  6. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 398
  7. 2023Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discoverycited by 336
  8. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  9. 2022Ask Me Anything: A simple strategy for prompting language modelscited by 155
  10. 2022Instruction Induction: From Few Examples to Natural Language Task Descriptionscited by 152
  11. 2024Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffoldingcited by 117
  12. 2023Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extractioncited by 89
5 more
  1. 2023Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RLcited by 37
  2. 2025Beyond English: The Impact of Prompt Translation Strategies across Languages and Tasks in Multilingual LLMscited by 22
  3. 2023NameGuess: Column Name Expansion for Tabular Datacited by 13
  4. 2025Knowledge Base Construction for Knowledge-Augmented Text-to-SQLcited by 9
  5. 2025Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Studycited by 6

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