# A Corpus for Multilingual Document Classification in Eight Languages

arXiv: https://arxiv.org/abs/1805.09821 · HTML: https://mlsanity.com/paper/1805.09821/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 May 2018.

## Built on by (most cited first, 30 of 42)

- [Spanish Pre-trained BERT Model and Evaluation Data](https://mlsanity.com/paper/2308.02976/) (2023)
- [A Primer on Pretrained Multilingual Language Models](https://mlsanity.com/paper/2107.00676/) (2021)
- [DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation](https://mlsanity.com/paper/2109.08877/) (2021)
- [Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models](https://mlsanity.com/paper/2103.08849/) (2021)
- [MarIA: Spanish Language Models](https://mlsanity.com/paper/2107.07253/) (2021)
- [AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models](https://mlsanity.com/paper/2404.16233/) (2024)
- [Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages](https://mlsanity.com/paper/2305.08487/) (2023)
- [EASE: Entity-Aware Contrastive Learning of Sentence Embedding](https://mlsanity.com/paper/2205.04260/) (2022)
- [Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models](https://mlsanity.com/paper/2205.06130/) (2022)
- [Multilingual and cross-lingual document classification: A meta-learning approach](https://mlsanity.com/paper/2101.11302/) (2021)
- [Preparing the Vuk'uzenzele and ZA-gov-multilingual South African multilingual corpora](https://mlsanity.com/paper/2303.03750/) (2023)
- [Spanish Legalese Language Model and Corpora](https://mlsanity.com/paper/2110.12201/) (2021)
- [X-METRA-ADA: Cross-lingual Meta-Transfer Learning Adaptation to Natural Language Understanding and Question Answering](https://mlsanity.com/paper/2104.09696/) (2021)
- [Beyond Static Models and Test Sets: Benchmarking the Potential of Pre-trained Models Across Tasks and Languages](https://mlsanity.com/paper/2205.06356/) (2022)
- [mCSQA: Multilingual Commonsense Reasoning Dataset with Unified Creation Strategy by Language Models and Humans](https://mlsanity.com/paper/2406.04215/) (2024)
- [A Dataset and Baselines for Multilingual Reply Suggestion](https://mlsanity.com/paper/2106.02017/) (2021)
- [Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling](https://mlsanity.com/paper/2104.05064/) (2021)
- [Lessons learned from the evaluation of Spanish Language Models](https://mlsanity.com/paper/2212.08390/) (2022)
- [T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification](https://mlsanity.com/paper/2306.04996/) (2023)
- [Understanding the effects of language-specific class imbalance in multilingual fine-tuning](https://mlsanity.com/paper/2402.13016/) (2024)
- [ALBETO and DistilBETO: Lightweight Spanish Language Models](https://mlsanity.com/paper/2204.09145/) (2022)
- [Polyglot Prompt: Multilingual Multitask PrompTraining](https://mlsanity.com/paper/2204.14264/) (2022)
- [Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks](https://mlsanity.com/paper/2210.09588/) (2022)
- [Lightweight Cross-Lingual Sentence Representation Learning](https://mlsanity.com/paper/2105.13856/) (2021)
- [RigoBERTa: A State-of-the-Art Language Model For Spanish](https://mlsanity.com/paper/2205.10233/) (2022)
- [Retrofitting Multilingual Sentence Embeddings with Abstract Meaning Representation](https://mlsanity.com/paper/2210.09773/) (2022)
- [Training Dynamics for Curriculum Learning: A Study on Monolingual and Cross-lingual NLU](https://mlsanity.com/paper/2210.12499/) (2022)
- [Cross-Lingual Transfer Robustness to Lower-Resource Languages on Adversarial Datasets](https://mlsanity.com/paper/2403.20056/) (2024)
- [Document Intelligence in the Era of Large Language Models: A Survey](https://mlsanity.com/paper/2510.13366/) (2025)
- [Improving Zero-Shot Cross-Lingual Transfer via Progressive Code-Switching](https://mlsanity.com/paper/2406.13361/) (2024)

## Abstract (arXiv)

Cross-lingual document classification aims at training a document classifier on resources in one language and transferring it to a different language without any additional resources. Several approaches have been proposed in the literature and the current best practice is to evaluate them on a subset of the Reuters Corpus Volume 2. However, this subset covers only few languages (English, German, French and Spanish) and almost all published works focus on the the transfer between English and German. In addition, we have observed that the class prior distributions differ significantly between the languages. We argue that this complicates the evaluation of the multilinguality. In this paper, we propose a new subset of the Reuters corpus with balanced class priors for eight languages. By adding Italian, Russian, Japanese and Chinese, we cover languages which are very different with respect to syntax, morphology, etc. We provide strong baselines for all language transfer directions using multilingual word and sentence embeddings respectively. Our goal is to offer a freely available framework to evaluate cross-lingual document classification, and we hope to foster by these means, research in this important area.