Domain-Specific QA System with Quantized Inverted Question Indexing and Adaptive Reasoning (RFT-26-0002)
Invention Summary
This invention presents a new design for domain-specific question-answering systems called QuIM-RAG. It improves Retrieval-Augmented Generation (RAG) pipelines by using inverted question matching. Instead of embedding document parts directly, the system uses a language model to create simple questions for each chunk, reflecting its main idea. These questions are then embedded, quantized, and stored in an organized index.
During query time, a user's natural language question is also embedded and quantized to match the closest prototype, enabling efficient and meaningful retrieval based on semantic intent. For complex queries, the system incorporates a divide-and-conquer mechanism that decomposes the query into sub-questions, applies multiple sanity checks for consistency and logic, and aggregates the results only if confidence thresholds are met. Otherwise, it invokes a fallback mechanism for clarification or human interaction. This innovation significantly improves retrieval accuracy, efficiency, and user trust by ensuring responses are relevant, context-aware, and of high confidence.
Overall Retrieval and Generation Architecture for RAG
Benefits
- Inverted question-based retrieval instead of chunk-based
- Embedding and quantization of representative questions for efficient prototype matching
- Semantic alignment via question intent rather than lexical similarity
- Divide-and-conquer mechanism for complex queries with multi-step sanity checks
- Confidence-calibrated fallback handling to avoid hallucinations
Applications
- Conversational AI assistants for universities and educational portals
- Customer service automation in regulated industries (banking, insurance)
- Clinical decision support or patient-facing chatbots
- Internal knowledge retrieval systems for corporations
- AI-based legal case summarizers and compliance tools
Patents
This technology has a Patent pending and is available for licensing/partnering opportunities.
Contact
NDSU Research Foundation
info(at)ndsurf(dot)org
(701)231-8173
NDSURF Tech Key
RFT, 260002, RFT260002
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