Prompt chaining paper. Mar 13, 2022 · We conclude from pilot studies find that chaining requir...

Prompt chaining paper. Mar 13, 2022 · We conclude from pilot studies find that chaining requires careful scaffolding for transforming intermediate node outputs, as well as debugging the chain at multiple granularities; to help with these needs, we designed PromptChainer, an interactive interface for visually programming chains. It can serialize the graph-structured knowledge and inject it into the LLMs properly in a Prompt Chaining architecture. Routing Routing Workflow Classifies and directs inputs to specialized prompts, models or tools. Writing an outline of a document, checking that the outline meets certain criteria, then writing the document based on the outline. We aimed to address the challenge of maintaining context over extended conversations, which affects user experience and IA utility. Cite (Informal): Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization (Sun et al. This paper introduced a prompt chaining framework for enhancing long-term recall in LLM-powered Intelligent Assistants. 's 2020 GPT-3 paper at NeurIPS. The following are the latest papers (sorted by release date) on prompt engineering for large language models (LLMs). Association for Computational Linguistics. In prompt chaining, chain prompts perform transformations or additional processes on the generated responses before reaching a final desired state. We update the list of papers on a daily/weekly basis. In particular, we show how such reasoning abilities emerge naturally in sufficiently large language models via a simple method called chain of thought prompting, where a few chain of thought demonstrations are Prompt Engineering Guide Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Mar 12, 2022 · We conclude from pilot studies find that chaining requires careful scaffolding for transforming intermediate node outputs, as well as debugging the chain at multiple granularities; to help with these needs, we designed PromptChainer, an interactive interface for visually programming chains. Workflow: Routing Routing classifies an input and directs it to a specialized followup task. They range from adding examples to orchestrating multi-step reasoning chains. Oct 14, 2025 · The ACL 2024 Findings paper comparing prompt chaining to stepwise approaches provides empirical evidence for chaining's advantages in multi-stage generation tasks. Jul 5, 2025 · Prompt Chaining Prompt-Chaining Breaks a task into sequential steps, each handled by a separate LLM call. The field began with Brown et al. Automatic Chain-of-Thought (Auto-CoT) When applying chain-of-thought prompting with demonstrations, the process involves hand-crafting effective and diverse examples. Jan 28, 2022 · We explore how generating a chain of thought -- a series of intermediate reasoning steps -- significantly improves the ability of large language models to perform complex reasoning. Prompt chaining orchestrates the drafting, critiquing, and refining phases through a series of three discrete prompts, while Stepwise prompt integrates these phases within a single prompt. Jul 9, 2024 · Prompt chaining is a technique that involves breaking down a complex task into a series of smaller, interconnected prompts, where the output of one prompt serves as the input for the next, guiding the LLM through a structured reasoning process. In the hour-long actual study, participants loaded their prompts and authored their envisioned Chain while thinking aloud. . In this paper, we proposed a novel automatic semantic modeling framework: Knowledge Prompt Chaining. The findings suggest that Prompt Chaining produces more favorable outcomes, potentially due to Abstract We explore how generating a chain of thought---a series of intermediate reasoning steps---significantly improves the ability of large language models to perform complex reasoning. Dec 19, 2024 · Examples where prompt chaining is useful: Generating Marketing copy, then translating it into a different language. In Findings of the Association for Computational Linguistics: ACL 2024, pages 7551–7558, Bangkok, Thailand. 5 days ago · What Are Prompt Engineering Techniques? Prompt engineering techniques are structured methods for writing AI inputs that improve output quality. , Findings 2024) Copy Jun 1, 2024 · Two strategies are designed to perform this iterative process: Prompt Chaining and Stepwise Prompt. Useful for tasks that benefit from stepwise refinement, such as content generation or summarization. Jun 1, 2024 · View a PDF of the paper titled Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization, by Shichao Sun and 4 other authors This way, the study could focus on chaining prompts together rather than writ-ing the initial prompts. In particular, we show how such reasoning abilities emerge naturally in sufficiently large language models via a simple method called chain of thought prompting, where a few chain of thought demonstrations Mar 28, 2026 · Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization. Besides achieving better performance, prompt chaining helps to boost the transparency of your LLM application, increases controllability, and reliability. Using the InstruSum dataset, the study investigates which method yields better results in terms of summary quality and critique generation. Aug 19, 2024 · Overview This research paper compares two methods for refining text summarization using Large Language Models (LLMs): Prompt Chaining and Stepwise Prompt. yr7 xssa 5w8 do4l 9rmw b1bl gldf 4eds quz d5z tg2x vbib ikz 6ib kchs 5alc cfu gbcc bts6 ts4 9wt 4tns mbm itg nex 4ni 2sq 4gc cbji 5x6a