Text Rewriting Model for Generative AI Hallucination Correction
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Solution Overview
Problem
Generative models often output misleading or factually incorrect text, known as hallucinations, even when citations to webpages are provided, leading users to incorrectly assume the text is supported by the cited content.
Innovation Solution
A system that monitors the output of a generative model, identifies citations and corresponding text, and uses a classifier to predict whether the text is factually accurate. If the text is not supported by the cited content, a text rewriting model generates a rewritten version of the text based on the original text and the cited content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a generative model generates text with citations to webpages, then the user can verify the accuracy of the text, but the generative model may still output misleading or factually incorrect text that is not supported by the cited content
Solution Approach 1:
The system implements a feedback mechanism where a classifier evaluates the alignment between generated text and cited webpage content. The classifier's prediction feeds back into a rewriting model that corrects misaligned text, creating a closed-loop system that continuously improves factual accuracy by comparing output against source material.
Solution Approach 2:
A classifier acts as an intermediary component between the generative model and the final output. This intermediary evaluates whether the generated text is properly supported by the cited content and triggers rewriting when mismatches are detected, serving as a quality control gate that prevents propagation of unsupported claims.
2Reliability
If a classifier is used to predict whether text is factually accurate, then the accuracy of the output can be improved, but the complexity of the system increases
Solution Approach 1:
The system segments the text generation and verification process into distinct functional modules: a generative model for text creation, a classifier for accuracy evaluation, and a rewriting model for correction. This segmentation allows each component to specialize in its function while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The classifier serves as an intermediary that bridges the generative model and final output without requiring complete system redesign. This intermediary approach enables incremental complexity addition, where the classifier and rewriting components are added as separate layers that build upon the existing generative model infrastructure.
3Reliability
If the text rewriting model generates rewritten text based on cited content, then the occurrence of misleading statements is reduced, but the time required to generate output increases
Solution Approach 1:
The system applies partial action by selectively rewriting only those text segments that the classifier identifies as factually inaccurate or unsupported by cited content. Rather than rewriting entire outputs, the system focuses computational resources on correcting specific problematic portions, reducing overall processing time while maintaining accuracy improvements.
Solution Approach 2:
The system skips the rewriting step when the classifier determines that the generated text is already factually accurate and properly supported by cited content. This conditional processing allows the system to rush through accurate segments without unnecessary rewriting operations, minimizing time penalties while preserving accuracy benefits for problematic text.
Data Source
AI summary
A computing system performs several acts, where the acts include providing text generated by a generative model and content of a webpage to a computer-implemented text rewriting model, where the generative model generated the text based upon user input received from a client computing device, and further where the generative model generated a citation to the webpage to indicate that the text generated by the generative model is supported by the content of the webpage. The acts also include generating, by the computer-implemented text rewriting model, a rewriting of the text, where the computer-implemented text rewriting model generates the rewriting of the text based upon: 1) the text generated by the generative model; and 2) the content of the webpage. The acts further include transmitting the rewriting of the text to the client computing device for presentment as a response to the user input received from the client computing device.