How does DL.Translator reduce 'hallucination' phenomena in AI translation?
“Large language models sometimes fabricate information or omit critical negations for the sake of fluency.”
Root Cause Analysis
Context-enhanced prompts
We do not simply send a single sentence to the AI. We package the surrounding contextual information of paragraphs together with document metadata, and apply extensively tested system prompts to ensure the model strictly adheres to the source text.
Multi-engine cross-verification (internal logic)
In advanced translation tasks, the system compares the translation outputs of different engines. If key data—such as numbers or dates—are inconsistent, the system will trigger a secondary verification mechanism.
Final Solution Summary
Although AI cannot completely eliminate hallucination, engineering solutions adopted by DL.Translator have reduced its occurrence to a level acceptable for professional office applications.