Accuracy-Gated Local LLM Question Answering
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Solution Overview
Problem
Local large-scale language models (LLMs) often generate responses with low accuracy, necessitating direct communication with a responder for a suitable response, which can be bothersome for the questioner.
Innovation Solution
A question answering device that includes a control unit to generate an initial response using a local LLM, determine its accuracy, and if low, seek a second response from a human respondent or a different LLM, ensuring an appropriate response is provided without bothering the questioner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a local LLM is used to generate responses, then responsiveness and data privacy are improved, but response accuracy deteriorates
Solution Approach 1:
The system incorporates a feedback mechanism where the accuracy of LLM-generated responses is evaluated, and when accuracy is insufficient, the system seeks correction from human responders or alternative LLMs. This feedback loop ensures that only accurate responses are provided to the questioner, resolving the contradiction between fast local generation and accurate response by continuously verifying and correcting outputs.
Solution Approach 2:
The system introduces an intermediary verification process between the local LLM and the final response output. This intermediary layer evaluates the accuracy of generated responses and mediates by consulting human responders or alternative models when necessary, thereby maintaining both the speed advantage of local processing and the accuracy requirement.
2Reliability
If a local LLM is used for question answering, then data privacy and autonomy are improved, but response quality deteriorates
Solution Approach 1:
The system implements feedback mechanisms that evaluate response quality and trigger corrections from human responders or alternative LLMs when the local model produces insufficient responses. This ensures high response quality while maintaining data privacy, as all processing occurs locally without compromising accuracy.
Solution Approach 2:
The system can switch between different LLM models or adjustment parameters when the initial response quality is insufficient. By changing the model parameters or selecting alternative models with different characteristics, the system maintains high response quality while preserving the data privacy advantages of local processing.
3Measurement precision
If direct communication with responder is required for inaccurate responses, then response accuracy is improved, but user experience deteriorates
Solution Approach 1:
The system performs self-service by automatically evaluating the accuracy of its own responses and initiating correction processes without requiring user intervention. When the local LLM generates an inaccurate response, the system autonomously seeks correction from human responders or alternative models, thereby maintaining high accuracy while preserving ease of operation for the user.
Solution Approach 2:
The feedback mechanism operates transparently in the background, automatically verifying response accuracy and correcting errors without involving the user in the process. This self-correcting feedback loop ensures high response accuracy while maintaining smooth user experience, as users simply interact with the system without being aware of the underlying verification and correction processes.
Data Source
AI summary
According to one embodiment, a question answering device includes a control unit and a communication interface connectable to a questioner terminal. The control unit id configured to receive a question from the questioner terminal via the communication interface, then generate a first response to the question using a first local large-scale language model (LLM). The control unit then generates an accuracy determination for the first response. The control unit provides the question to a second response generation unit if the accuracy determination indicates accuracy of the first response is low, and then sends a second response to the questioner terminal via the communication interface if the second response is received from the second response generation unit after the accuracy determination indicates the accuracy of the first response is low.