MIDAS: Multi-LLM Iterative Data-Adaptive Summarization
3.20T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.04307.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA research paper proposing MIDAS, a multi-LLM framework for text summarization that adapts to different summary requirements without manual prompt engineering. It outperforms critique-driven baselines such as CriSPO and ZERA on enterprise ticket summarization across five output formats and demonstrates cross-domain generalization to finance.
Why it mattersA concrete multi-LLM orchestration pattern that eliminates manual prompt engineering for domain-specific summarization, with measured gains over existing critique-based optimization methods.
Cited by
No citations on record.