# Cross-genre Document Retrieval: Matching between Conversational and Formal Writings

arXiv: https://arxiv.org/abs/1707.04538 · HTML: https://mlsanity.com/paper/1707.04538/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2017.

## Built on by (most cited first, 1 of 1)

- [Where Does Retrieval Fail? Evaluating RAG Architectures for Agricultural Advisory](https://mlsanity.com/paper/2608.14886/) (2026)

## Abstract (arXiv)

This paper challenges a cross-genre document retrieval task, where the queries are in formal writing and the target documents are in conversational writing. In this task, a query, is a sentence extracted from either a summary or a plot of an episode in a TV show, and the target document consists of transcripts from the corresponding episode. To establish a strong baseline, we employ the current state-of-the-art search engine to perform document retrieval on the dataset collected for this work. We then introduce a structure reranking approach to improve the initial ranking by utilizing syntactic and semantic structures generated by NLP tools. Our evaluation shows an improvement of more than 4% when the structure reranking is applied, which is very promising.