# Investigating Expert-in-the-Loop LLM Discourse Patterns for Ancient Intertextual Analysis

arXiv: https://arxiv.org/abs/2409.01882 · HTML: https://mlsanity.com/paper/2409.01882/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 30 references that are in the map.
- First posted on arXiv 3 Sep 2024.

## Builds on (most cited first, 8 of 8)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis](https://mlsanity.com/paper/2310.15100/) (2023)
- [Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review](https://mlsanity.com/paper/2204.10805/) (2022)
- [How Powerful are Decoder-Only Transformer Neural Models?](https://mlsanity.com/paper/2305.17026/) (2023)
- [Automating Thematic Analysis: How LLMs Analyse Controversial Topics](https://mlsanity.com/paper/2405.06919/) (2024)
- [Large Language Model Recall Uncertainty is Modulated by the Fan Effect](https://mlsanity.com/paper/2407.06349/) (2024)

## Built on by (most cited first, 4 of 4)

- [LLMs-in-the-Loop Part 2: Expert Small AI Models for Anonymization and De-identification of PHI Across Multiple Languages](https://mlsanity.com/paper/2412.10918/) (2024)
- [Quantitative Intertextuality from the Digital Humanities Perspective: A Survey](https://mlsanity.com/paper/2510.27045/) (2025)
- ['The Order in the Horse's Heart': A Case Study in LLM-Assisted Stylometry for the Discovery of Biblical Allusion in Modern Literary Fiction](https://mlsanity.com/paper/2604.19447/) (2026)
- [Retrieving Biblical Intertextual References in Karen Blixen's Seven Gothic Tales](https://mlsanity.com/paper/2609.35765/) (2026)

## Abstract (arXiv)

This study explores the potential of large language models (LLMs) for identifying and examining intertextual relationships within biblical, Koine Greek texts. By evaluating the performance of LLMs on various intertextuality scenarios the study demonstrates that these models can detect direct quotations, allusions, and echoes between texts. The LLM's ability to generate novel intertextual observations and connections highlights its potential to uncover new insights. However, the model also struggles with long query passages and the inclusion of false intertextual dependences, emphasizing the importance of expert evaluation. The expert-in-the-loop methodology presented offers a scalable approach for intertextual research into the complex web of intertextuality within and beyond the biblical corpus.