Information Processing for Guided LLM Summarization and Translation
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Solution Overview
Problem
Existing information processing systems struggle with varying writing styles in product descriptions, leading to inconsistent and suboptimal summarization and translation of transaction objects, which hinders user comparison and understanding.
Innovation Solution
An information processing system that utilizes large language model servers to obtain descriptions, apply guidelines for summarization and translation, and evaluate the results to ensure accuracy and consistency, using multiple models and stages to refine summaries and translations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If administrators elaborate expressions in descriptions to communicate product attractiveness, then the descriptiveness and appeal of products is improved, but the writing style consistency and summarization accuracy deteriorates
Solution Approach 1:
The patent segments the summarization process into multiple stages: first extracting key information points from the original description, then generating summaries that standardize the format while preserving the essential product attributes. This segmentation allows the system to handle diverse writing styles in the input while producing consistent, standardized outputs.
Solution Approach 2:
The patent applies parameter changes by transforming the input descriptions through controlled modification of their structural parameters. The system changes the format, tone, and organization parameters of the descriptions to achieve standardization while maintaining the core product information and appeal conveyed by the administrators.
2Device complexity
If the system processes only original texts without guidelines, then the processing simplicity is maintained, but the summary consistency and quality deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-defining summary guidelines and templates before processing the actual descriptions. These guidelines establish the expected format, structure, and key information points that must be included in the summaries, enabling consistent processing without adding complexity to the core summarization mechanism.
Solution Approach 2:
The system incorporates feedback mechanisms where the generated summaries are evaluated against the predefined guidelines and original descriptions. This feedback loop allows the system to adjust and refine its summarization process, ensuring consistency and quality while maintaining processing simplicity through automated validation.
Data Source
AI summary
An information processing method causes one or multiple computers to obtain a description of a transaction object input by an administrator of the transaction object, obtain a guideline related to a summary of the description, and transmit the description and the guideline to a summarization model to obtain a summary of the description.