# Knowledge-Aware Diverse Reranking for Cross-Source Question Answering

Source: [Knowledge-Aware Diverse Reranking for Cross-Source Question Answering](<https://www.sota2.com/research/paper/68fa79a01e209131cea7e82a>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T05:01:45.766Z

Authors: Tong Zhou

Published: 2025-06-25T14:23:21.000Z

## Abstract

This paper presents Team Marikarp's solution for the SIGIR 2025 LiveRAG competition. The competition's evaluation set, automatically generated by DataMorgana from internet corpora, encompassed a wide range of target topics, question types, question formulations, audience types, and knowledge organization methods. It offered a fair evaluation of retrieving question-relevant supporting documents from a 15M documents subset of the FineWeb corpus. Our proposed knowledge-aware diverse reranking RAG pipeline achieved first place in the competition.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2506.20476>)

[PDF](<https://arxiv.org/pdf/2506.20476.pdf>)