ACL Findings2026
Disentangling Codemixing in Chats: The NUS ABC Codemixed Corpus
Svetlana Churina, Akshat Gupta, Nur Insyirah Binte Imam Mujtahid, Kokil Jaidka
Abstract
Code-mixing involves the seamless integration of linguistic elements from multiple languages within a single discourse, reflecting natural multilingual communication patterns. Despite its prominence in informal interactions such as social media, chat messages and instantmessaging exchanges, there has been a lack of publicly available corpora that are authorlabeled and suitable for modeling human conversations and relationships. This study introduces the first labeled and general-purpose corpus for understanding code-mixing in context while maintaining rigorous privacy and ethical standards. It includes over 355,641 messages spanning various code-mixing patterns, with a primary focus on English, Mandarin, and other languages. We expect the Codemix Corpus to serve as a foundational dataset for research in computational linguistics, sociolinguistics, and NLP applications. Code and dataset sample can be found here.
Ask Lune
Ask anything. The answer quotes the paper.
Lune reads all of it and the papers around it, then shows you the passages behind every answer.
Builds on2
- Multilingual Large Language Models Are Not (Yet) Code-SwitchersRuochen Zhang, Samuel Cahyawijaya, Jan Christian Blaise Cruz, Genta Indra Winata et al.EMNLP 2023 · 19 citations
- In-context Mixing (ICM): Code-mixed Prompts for Multilingual LLMsBhavani Shankar, Preethi Jyothi, Pushpak BhattacharyyaACL 2024
Related papers
- SyMCoM - Syntactic Measure of Code Mixing A Study Of English-Hindi Code-MixingPrashant Kodali, Anmol Goel, Monojit Choudhury, Manish Shrivastava et al.ACL Findings 2022 · 1 citation
- CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 LanguagesYilun Yang, Yekun ChaiEMNLP 2025 · 1 citation
- A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer LearningDeepak Gupta, Asif Ekbal, Pushpak BhattacharyyaEMNLP Findings 2020 · 44 citations
- Tell me Habibi, is it Real or Fake?Kartik Kuckreja, Parul Gupta, Injy Hamed, Thamar Solorio et al.ICLR 2026 · 10 citations
- Automatic Identification of Code-Switching Functions in Speech TranscriptsRitu Belani, Jeffrey FlaniganACL Findings 2023 · 1 citation
