# Loci Similes: A Benchmark for Extracting Intertextualities in Latin Literature

arXiv: https://arxiv.org/abs/2601.07533 · HTML: https://mlsanity.com/paper/2601.07533/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 63 references that are in the map.
- First posted on arXiv 12 Jan 2026.

## Builds on (most cited first, 22 of 22)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://mlsanity.com/paper/2004.12832/) (2020)
- [M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation](https://mlsanity.com/paper/2402.03216/) (2024)
- [Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference](https://mlsanity.com/paper/2412.13663/) (2024)
- [One Embedder, Any Task: Instruction-Finetuned Text Embeddings](https://mlsanity.com/paper/2212.09741/) (2022)
- [mmBERT: A Modern Multilingual Encoder with Annealed Language Learning](https://mlsanity.com/paper/2509.06888/) (2025)
- [The birth of Romanian BERT](https://mlsanity.com/paper/2009.08712/) (2020)
- [Latin BERT: A Contextual Language Model for Classical Philology](https://mlsanity.com/paper/2009.10053/) (2020)
- [How Large Language Models are Transforming Machine-Paraphrased Plagiarism](https://mlsanity.com/paper/2210.03568/) (2022)
- [Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review](https://mlsanity.com/paper/2204.10805/) (2022)
- [Paraphrase Detection: Human vs. Machine Content](https://mlsanity.com/paper/2303.13989/) (2023)
- [DirectQuote: A Dataset for Direct Quotation Extraction and Attribution in News Articles](https://mlsanity.com/paper/2110.07827/) (2021)
- [On the Feasibility of Automated Detection of Allusive Text Reuse](https://mlsanity.com/paper/1905.02973/) (2019)
- [Reception Reader: Exploring Text Reuse in Early Modern British Publications](https://mlsanity.com/paper/2302.04084/) (2023)
- [Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature](https://mlsanity.com/paper/2308.12008/) (2023)
- [Mining Asymmetric Intertextuality](https://mlsanity.com/paper/2410.15145/) (2024)
- [Latent Structures of Intertextuality in French Fiction](https://mlsanity.com/paper/2410.17759/) (2024)
- [BiMax: Bidirectional MaxSim Score for Document-Level Alignment](https://mlsanity.com/paper/2510.15577/) (2025)
- [Metric Learning in Multilingual Sentence Similarity Measurement for Document Alignment](https://mlsanity.com/paper/2108.09495/) (2021)
- [Latin writing styles analysis with Machine Learning: New approach to old questions](https://mlsanity.com/paper/2109.00601/) (2021)

## Built on by (most cited first, 3 of 3)

- [Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke](https://mlsanity.com/paper/2605.09236/) (2026)
- [From transcription to semantic corpus analysis: unsupervised learning of sentence representations for ancient languages](https://mlsanity.com/paper/2607.24542/) (2026)
- [Beyond Similarity: Grounded Agentic Extraction and Expert-Adjudicated Evaluation of Intertextuality in Classical Chinese Histories](https://mlsanity.com/paper/2607.27595/) (2026)

## Abstract (arXiv)

Tracing connections between historical texts is an important part of intertextual research, enabling scholars to reconstruct the virtual library of a writer and identify the sources influencing their creative process. These intertextual links manifest in diverse forms, ranging from direct verbatim quotations to subtle allusions and paraphrases disguised by morphological variation. Language models offer a promising path forward due to their capability of capturing semantic similarity beyond lexical overlap. However, the development of new methods for this task is held back by the scarcity of standardized benchmarks and easy-to-use datasets. We address this gap by introducing Loci Similes, a benchmark for Latin intertextuality detection comprising a curated dataset of ~176k text segments and 1,490 expert-verified parallels, including 945 labeled references from an existing dataset. Using this data, we establish baselines for retrieval and classification of intertextualities with both lexical methods and pretrained encoder language models.