Evidence-Unit Fairness and the Limits of Query-Adaptive Sparse-Dense Fusion in Financial Document Retrieval
The episode discusses 'Evidence-Unit Fairness and the Limits of Query-Adaptive Sparse-Dense Fusion' for financial document retrieval. Hosts analyze how current fusion methods can be biased, focusing on quantifying failure modes and proposing architectural shifts to ensure retrieval is fair, balanced, and trustworthy.