IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Not on the map. Why?
Abstract (arXiv)
Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixed with Indonesian in daily conversation. In this work, we explore code-mixing in Indonesian with four embedded languages, i.e., English, Sundanese, Javanese, and Malay; and introduce IndoRobusta, a framework to evaluate and improve the code-mixing robustness. Our analysis shows that the pre-training corpus bias affects the model's ability to better handle Indonesian-English code-mixing when compared to other local languages, despite having higher language diversity.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 31 of its 54 references that are in the map. First posted on arXiv 21 Nov 2023.
Builds on
31 of 54 references.
References · 31
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2018Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labelscited by 997
- 2019Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailmentcited by 671
- 2020GLUECoS : An Evaluation Benchmark for Code-Switched NLPcited by 102
- 2020LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluationcited by 93
- 2020CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLPcited by 79
- 2021NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentationcited by 73
- 2022NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languagescited by 68
- 2022One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesiacited by 66
- 2020IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLPcited by 58
19 more
- 2021IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generationcited by 57
- 2021Are Multilingual Models Effective in Code-Switching?cited by 56
- 2021BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modelingcited by 56
- 2021Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitutioncited by 56
- 2019Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentencescited by 55
- 2021ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversationcited by 44
- 2018Code-switching Sentence Generation by Generative Adversarial Networks and its Application to Data Augmentationcited by 26
- 2021Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglotscited by 23
- 2020Meta-Transfer Learning for Code-Switched Speech Recognitioncited by 22
- 2020Improving Bi-LSTM Performance for Indonesian Sentiment Analysis Using Paragraph Vectorcited by 18
- 2018A Dataset for Building Code-Mixed Goal Oriented Conversation Systemscited by 16
- 2019Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translationcited by 16
- 2018Code-Switching Language Modeling using Syntax-Aware Multi-Task Learningcited by 15
- 2020Efficient Estimation of Influence of a Training Instancecited by 11
- 2021Model Generalization on COVID-19 Fake News Detectioncited by 11
- 2022CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognitioncited by 10
- 2021CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixingcited by 8
- 2022Can Question Rewriting Help Conversational Question Answering?cited by 8
- 2019Code-switching Language Modeling With Bilingual Word Embeddings: A Case Study for Egyptian Arabic-Englishcited by 6
Built on by
Citing papers per year: 2024: 2; 2025: 2; 2026: 1.
5 papers.
- 2025The Multilingual Divide and Its Impact on Global AI Safetycited by 10
- 2025NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scriptscited by 4
- 2024Constructing and Expanding Low-Resource and Underrepresented Parallel Datasets for Indonesian Local Languagescited by 3
- 2026PingPong: A Natural Benchmark for Multi-Turn Code-Switching Dialoguescited by 1
- 2024NusaBERT: Teaching IndoBERT to be Multilingual and Multiculturalcited by 0
- 2026PingPong: A Natural Benchmark for Multi-Turn Code-Switching Dialogues24 Jan 2026
- 2025The Multilingual Divide and Its Impact on Global AI Safety27 May 2025
- 2025NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts25 Feb 2025
- 2024Constructing and Expanding Low-Resource and Underrepresented Parallel Datasets for Indonesian Local Languages1 Apr 2024
- 2024NusaBERT: Teaching IndoBERT to be Multilingual and Multicultural4 Mar 2024