AI Response Verification via Comparator Model
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Generative AI models often produce hallucinations, providing factually incorrect or nonsensical information due to the complexity of language understanding and generation, and current approaches are reactive and unable to proactively prevent such inaccuracies.
Innovation Solution
A two-point comparator model that uses predefined verified prompt-response pairs to proactively verify generative AI model responses and filter out hallucinations before they are presented to users, and also verifies user feedback to ensure its accuracy before applying it to AI model training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generative AI models are used to automate customer support tasks, then productivity and efficiency are improved, but hallucinations occur resulting in factually incorrect information being presented to users
Solution Approach 1:
A verification system acts as an intermediary between the generative AI model and the user. This system includes a comparator that compares AI-generated responses against a knowledge base to verify factual accuracy, and a feedback mechanism that provides correction signals. The intermediary structure allows the system to maintain high automation efficiency while filtering out hallucinated information before it reaches users.
Solution Approach 2:
The patent implements a feedback loop where user interactions and verification results are fed back to the generative AI model. When hallucinations are detected by the verification system, correction feedback is provided to the model, enabling it to learn from errors and improve response accuracy over time while maintaining automated operation.
2Reliability
If reactive processes are used to correct hallucinations after they occur, then some errors are fixed, but the correction process is delayed and users may already receive incorrect information
Solution Approach 1:
The verification system performs preliminary checks on AI-generated responses before they are presented to users. The comparator proactively compares generated content against the knowledge base in advance, identifying and flagging potential hallucinations before user interaction occurs. This preliminary verification eliminates the time delay inherent in reactive correction approaches.
3Adaptability or versatility
If the generative AI model generates highly creative and flexible responses, then user satisfaction improves, but the likelihood of hallucinations increases
Solution Approach 1:
The verification system applies different verification strategies to different parts of the response. Critical factual claims are rigorously checked against the knowledge base, while creative or subjective portions are evaluated with appropriate flexibility. This localized verification approach maintains response creativity and adaptability while ensuring factual accuracy where required.
Data Source
AI summary
A method, computer program product, and computing system for processing a prompt for a target generative AI model and a corresponding response generated by the target generative AI model for the prompt. The prompt and the corresponding response from the generative AI model are compared to a plurality of predefined verified prompt-response pairs. In response to determining at least a threshold similarity between the prompt and the corresponding response and a predefined verified prompt-response pair, the corresponding response from the target generative AI model is provided to a source of the prompt.