Language Model Learning Progress via Answer Similarity Checks
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Solution Overview
Problem
Existing language models struggle to automatically determine the progress of learning, leading to insufficient or excessive data acquisition, which affects their ability to accurately interpret industry-specific expressions, thereby increasing costs and inefficiencies.
Innovation Solution
An information processing apparatus and method that includes a generation control unit to input question sentences to a language model and a determination unit to compare generated answer sentences with and without reference to a target document, determining similarity to assess learning progress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data to be learned is excessively acquired, then the language model can be trained more comprehensively, but the cost of learning and data preparation increases
Solution Approach 1:
The patent implements a feedback mechanism by comparing the language model's answers before and after learning to automatically determine learning progress. This feedback loop enables dynamic adjustment of data acquisition, stopping when learning objectives are achieved rather than continuously acquiring excessive data, thus resolving the contradiction between learning completeness and data volume.
2Reliability
If data to be learned is excessively acquired, then the language model can be trained more comprehensively, but the cost of preparing data to be learned increases
Solution Approach 1:
The automatic determination mechanism provides real-time feedback on learning progress by comparing answer similarities, enabling early termination of data preparation when learning objectives are met. This prevents wasteful expenditure of resources on preparing excessive data, resolving the contradiction between learning completeness and preparation cost.
3Measurement precision
If the language model learning progress cannot be automatically determined, then manual monitoring is required, but this reduces productivity and increases time consumption
Solution Approach 1:
The patent enables the language model learning system to self-monitor its own progress by automatically comparing answers generated before and after learning. This self-service mechanism eliminates the need for manual monitoring, simultaneously achieving precise learning progress measurement and maintaining high productivity, thus resolving the contradiction between measurement precision and learning efficiency.
Data Source
AI summary
An information processing apparatus includes at least one memory that stores instructions and at least one processor that executes the instructions. The at least one processor executes the instructions to: input a question sentence about a content of a targeted document to a language model generated by machine learning to generate an answer sentence to a question about the content of the document to cause the language model to generate a first answer sentence; and determine a similarity between a second answer sentence to the question sentence, the second answer sentence being generated by causing the language model to refer to at least a part of the document, and the first answer sentence.