Four measures are needed to reduce hallucinations in academic settings:
- Enable RAT mode: By
RATPipelineconfigurereasoning_model_name="deepseek-r1:1.5b"cap (a poem)reflection=2Enhanced fact-checking - Source labeling: in
RAGPipelineSet at initializationreturn_sources=TrueThe output will be accompanied by the location of the references. - Document Cleaning: Remove non-text content (e.g. headers and footers) when pre-processing PDFs to reduce noise interference
- parameter tuning::
- raise
k=7Get more supporting materials - Set the LLM's
temperature=0.3Reduced randomness
- raise
It is recommended that manual sampling of key findings be implemented and that an accuracy assessment mechanism be established for continuous optimization.
This answer comes from the articleRAGLight: Lightweight Retrieval Augmentation Generation Python LibraryThe
May not be reproduced without permission:AI productivity tools " How to eliminate RAGLight's phantom problem in scholarly literature processing?
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