Commentator: A Code-mixed Multilingual Text Annotation Framework (2024.emnlp-demo)
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| Challenge: | Existing annotation tools fail to address multilingual datasets efficiently. |
| Approach: | They introduce a code-mixed multilingual text annotation framework, COMMENTATOR . they perform robust qualitative human-based evaluations to showcase its effectiveness . |
| Outcome: | The proposed framework performs faster than baseline annotations in Hinglish and Hindi. |
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Processing and Understanding Mixed Language Data (D19-2)
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| Challenge: | Multilingual communities exhibit code-mixing, mixing of two or more languages in a single conversation . social media and other informal interactive platforms are allowing code-switching in user-generated text . |
| Approach: | a tutorial aims to provide a foundation for researchers to study code-mixing in multilingual communities. |
| Outcome: | a tutorial aims to provide new researchers with a foundation in linguistics and computational aspects of code-mixing. |
CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations (2025.findings-acl)
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| Challenge: | Discourse parsing datasets based on conversations are restricted to a single domain . a lack of discourse structures in audio-based conversations is a challenge . |
| Approach: | They introduce CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse parsing in conversations. |
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The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)
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| Challenge: | Until recently, language descriptions were available in paper form only, with indexes as the only search aid. |
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Wikinflection Corpus: A (Better) Multilingual, Morpheme-Annotated Inflectional Corpus (2020.lrec-1)
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| Challenge: | Inflectional corpora with annotated morpheme boundaries are scarce in the NLP community . a generated, multilingual inflectional lexicon with morphological features is not as good as UniMorph's . |
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Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models (2025.emnlp-main)
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Mehdi Ali, Manuel Brack, Max Lübbering, Elias Wendt, Abbas Goher Khan, Richard Rutmann, Alex Jude, Maurice Kraus, Alexander Arno Weber, Felix Stollenwerk, David Kaczér, Florian Mai, Lucie Flek, Rafet Sifa, Nicolas Flores-Herr, Joachim Koehler, Patrick Schramowski, Michael Fromm, Kristian Kersting
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Language Agnostic Code Embeddings (2024.naacl-long)
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| Challenge: | Recent studies show that code language models have strong cross-lingual traits, but their multilingual representations can be dissected into a language-specific syntax component and a semantic component. |
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COMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing (2025.findings-emnlp)
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| Challenge: | COMI-LINGUA is the largest manually annotated Hindi-English code-mixed dataset . 125K+ high-quality instances across five core NLP tasks are annotating by three bilingual annotators . |
| Approach: | COMI-LINGUA is the largest manually annotated Hindi-English code-mixed dataset . 125K+ high-quality instances are annotating by three bilingual annotators . |
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Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation (2025.acl-long)
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Shivalika Singh, Angelika Romanou, Clémentine Fourrier, David Ifeoluwa Adelani, Jian Gang Ngui, Daniel Vila-Suero, Peerat Limkonchotiwat, Kelly Marchisio, Wei Qi Leong, Yosephine Susanto, Raymond Ng, Shayne Longpre, Sebastian Ruder, Wei-Yin Ko, Antoine Bosselut, Alice Oh, Andre Martins, Leshem Choshen, Daphne Ippolito, Enzo Ferrante, Marzieh Fadaee, Beyza Ermis, Sara Hooker
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Towards Responsible Natural Language Annotation for the Varieties of Arabic (2022.findings-acl)
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| Challenge: | In NLP, there is a tendency to aim for broader coverage, often overlooking cultural and (socio)linguistic nuance. |
| Approach: | They propose a playbook for responsible dataset creation for polyglossic, multidialectal languages . they focus on Arabic annotation of social media content as an example . |
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hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization (2020.coling-industry)
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| Challenge: | hinglishNorm is a human annotated corpus of Hindi-English code-mixed sentences for text normalization task. |
| Approach: | They propose to annotate sentences in Hindi-English code-mixed sentences using a human annotated normalized form. |
| Outcome: | The proposed corpus contains 13494 segments annotated for text normalization. |