Venn Diagram Prompting : Accelerating Comprehension with Scaffolding Effect

TL;DR

Venn Diagram Prompting is a novel technique that enables large language models to synthesize information across multiple documents in a single step, improving answer consistency and performance in knowledge-intensive tasks.

Contribution

The paper introduces Venn Diagram Prompting, a single-call method that replaces multi-step approaches and reduces position bias in LLM-based question answering.

Findings

VD prompting matches or exceeds traditional instruction prompts in benchmarks.

It reduces answer inconsistency caused by input sequence sensitivity.

The method enhances the quality and reliability of LLM responses.

Abstract

We introduce Venn Diagram (VD) Prompting, an innovative prompting technique which allows Large Language Models (LLMs) to combine and synthesize information across complex, diverse and long-context documents in knowledge-intensive question-answering tasks. Generating answers from multiple documents involves numerous steps to extract relevant and unique information and amalgamate it into a cohesive response. To improve the quality of the final answer, multiple LLM calls or pretrained models are used to perform different tasks such as summarization, reorganization and customization. The approach covered in the paper focuses on replacing the multi-step strategy via a single LLM call using VD prompting. Our proposed technique also aims to eliminate the inherent position bias in the LLMs, enhancing consistency in answers by removing sensitivity to the sequence of input information. It overcomes the challenge of inconsistency traditionally associated with varying input sequences. We also explore the practical applications of the VD prompt based on our examination of the prompt's outcomes. In the experiments performed on four public benchmark question-answering datasets, VD prompting continually matches or surpasses the performance of a meticulously crafted instruction prompt which adheres to optimal guidelines and practices.