# A Novel Cartography-Based Curriculum Learning Method Applied on RoNLI: The First Romanian Natural Language Inference Corpus

arXiv: https://arxiv.org/abs/2405.11877 · HTML: https://mlsanity.com/paper/2405.11877/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 57 references that are in the map.
- First posted on arXiv 20 May 2024.

## Builds on (most cited first, 27 of 27)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding](https://mlsanity.com/paper/1804.07461/) (2018)
- [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://mlsanity.com/paper/1606.05250/) (2016)
- [A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://mlsanity.com/paper/1704.05426/) (2017)
- [A large annotated corpus for learning natural language inference](https://mlsanity.com/paper/1508.05326/) (2015)
- [SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems](https://mlsanity.com/paper/1905.00537/) (2019)
- [Enriching Word Vectors with Subword Information](https://mlsanity.com/paper/1607.04606/) (2016)
- [XNLI: Evaluating Cross-lingual Sentence Representations](https://mlsanity.com/paper/1809.05053/) (2018)
- [Adversarial NLI: A New Benchmark for Natural Language Understanding](https://mlsanity.com/paper/1910.14599/) (2019)
- [Annotation Artifacts in Natural Language Inference Data](https://mlsanity.com/paper/1803.02324/) (2018)
- [Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics](https://mlsanity.com/paper/2009.10795/) (2020)
- [Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://mlsanity.com/paper/1909.00161/) (2019)
- [Lessons from Natural Language Inference in the Clinical Domain](https://mlsanity.com/paper/1808.06752/) (2018)
- [ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://mlsanity.com/paper/2110.01799/) (2021)
- [OCNLI: Original Chinese Natural Language Inference](https://mlsanity.com/paper/2010.05444/) (2020)
- [The birth of Romanian BERT](https://mlsanity.com/paper/2009.08712/) (2020)
- [SciNLI: A Corpus for Natural Language Inference on Scientific Text](https://mlsanity.com/paper/2203.06728/) (2022)
- [Figurative Language in Recognizing Textual Entailment](https://mlsanity.com/paper/2106.01195/) (2021)
- [NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning](https://mlsanity.com/paper/2105.14167/) (2021)
- [IndoNLI: A Natural Language Inference Dataset for Indonesian](https://mlsanity.com/paper/2110.14566/) (2021)
- [JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset](https://mlsanity.com/paper/2212.03419/) (2022)
- [Entailment Semantics Can Be Extracted from an Ideal Language Model](https://mlsanity.com/paper/2209.12407/) (2022)
- [RoDia: A New Dataset for Romanian Dialect Identification from Speech](https://mlsanity.com/paper/2309.03378/) (2023)
- [InferES : A Natural Language Inference Corpus for Spanish Featuring Negation-Based Contrastive and Adversarial Examples](https://mlsanity.com/paper/2210.03068/) (2022)
- [Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5](https://mlsanity.com/paper/2210.17301/) (2022)

## Built on by (most cited first, 8 of 8)

- [mSTEB: Massively Multilingual Evaluation of LLMs on Speech and Text Tasks](https://mlsanity.com/paper/2506.08400/) (2025)
- [Soft Language Prompts for Language Transfer](https://mlsanity.com/paper/2407.02317/) (2024)
- [SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe](https://mlsanity.com/paper/2410.05248/) (2024)
- [Task-Informed Anti-Curriculum by Masking Improves Downstream Performance on Text](https://mlsanity.com/paper/2502.12953/) (2025)
- [DynClean: Training Dynamics-based Label Cleaning for Distantly-Supervised Named Entity Recognition](https://mlsanity.com/paper/2504.04616/) (2025)
- [LLM-Guided Co-Training for Text Classification](https://mlsanity.com/paper/2509.16516/) (2025)
- [CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning](https://mlsanity.com/paper/2601.05858/) (2026)
- [Disentangling Curriculum Learning in NLP: Towards a Unifying Taxonomy](https://mlsanity.com/paper/2607.18984/) (2026)

## Abstract (arXiv)

Natural language inference (NLI), the task of recognizing the entailment relationship in sentence pairs, is an actively studied topic serving as a proxy for natural language understanding. Despite the relevance of the task in building conversational agents and improving text classification, machine translation and other NLP tasks, to the best of our knowledge, there is no publicly available NLI corpus for the Romanian language. To this end, we introduce the first Romanian NLI corpus (RoNLI) comprising 58K training sentence pairs, which are obtained via distant supervision, and 6K validation and test sentence pairs, which are manually annotated with the correct labels. We conduct experiments with multiple machine learning methods based on distant learning, ranging from shallow models based on word embeddings to transformer-based neural networks, to establish a set of competitive baselines. Furthermore, we improve on the best model by employing a new curriculum learning strategy based on data cartography. Our dataset and code to reproduce the baselines are available at https://github.com/Eduard6421/RONLI.