mlsanityData to 7 Oct 2026

NLAS-multi: A Multilingual Corpus of Automatically Generated Natural Language Argumentation Schemes

arXiv 2402.14458 ↗First posted 22 Feb 2024cs.CL cs.AIcited by 5

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Abstract (arXiv)

Some of the major limitations identified in the areas of argument mining, argument generation, and natural language argument analysis are related to the complexity of annotating argumentatively rich data, the limited size of these corpora, and the constraints that represent the different languages and domains in which these data is annotated. To address these limitations, in this paper we present the following contributions: (i) an effective methodology for the automatic generation of natural language arguments in different topics and languages, (ii) the largest publicly available corpus of natural language argumentation schemes, and (iii) a set of solid baselines and fine-tuned models for the automatic identification of argumentation schemes.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 47 references that are in the map. First posted on arXiv 22 Feb 2024.

Builds on

20 of 47 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2017Deep reinforcement learning from human preferencescited by 3,846
  6. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  7. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
  8. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
  9. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
  10. 2019Argument Generation with Retrieval, Planning, and Realizationcited by 45
  11. 2020Aspect-Controlled Neural Argument Generationcited by 43
  12. 2018Neural Argument Generation Augmented with Externally Retrieved Evidencecited by 34
8 more
  1. 2022BERTIN: Efficient Pre-Training of a Spanish Language Model using Perplexity Samplingcited by 30
  2. 2021Argument Undermining: Counter-Argument Generation by Attacking Weak Premisescited by 22
  3. 2020Multilingual Argument Mining: Datasets and Analysiscited by 19
  4. 2021Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemescited by 17
  5. 2020The workweek is the best time to start a family -- A Study of GPT-2 Based Claim Generationcited by 15
  6. 2023ArgU: A Controllable Factual Argument Generatorcited by 7
  7. 2021Knowledge-Enhanced Evidence Retrieval for Counterargument Generationcited by 6
  8. 2021Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Workscited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 2.

5 papers.

  1. 2024Critical Questions Generation: Motivation and Challengescited by 3
  2. 2024Understanding Enthymemes in Argument Maps: Bridging Argument Mining and Logic-based Argumentationcited by 2
  3. 2025DayDreamer at CQs-Gen 2025: Generating Critical Questions through Argument Scheme Completioncited by 0
  4. 2026CAF-Gen: A Multi-Agent System for Enriching Argumentation Structurescited by 0
  5. 2026Show Me How You Reason and I'll Tell You Who You Are: Reasoning Graphs for Robust LLM Authorship Attributioncited by 0