DPR-BAG generates factually grounded biomedical abstracts from full texts via structured BOMRC decomposition, parallel LLM prompting, and coherence refinement without any model training.
Proceedings of the AAAI Conference on Artificial Intelligence , author=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Divide-Prompt-Refine: a Training-Free, Structure-Aware Framework for Biomedical Abstract Generation
DPR-BAG generates factually grounded biomedical abstracts from full texts via structured BOMRC decomposition, parallel LLM prompting, and coherence refinement without any model training.