Who cites «A Survey of Corpora for Germanic Low-Resource Languages and Dialects»
22 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card
- Beyond Subtokens: A Rich Character Embedding for Low-resource and Morphologically Complex Languages — 2026 · arXiv:2602.21377
- Bi-Text Mining across German Dialects: On the Role of Synthetic Training Data for Dialect Adaptation — 2026 · Proceedings of the 19th Workshop on Building and Using Comparable Corpora (BUCC)
- CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Meenz bleibt Meenz, but Large Language Models Do Not Speak Its Dialect — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
- Mining Naturally Romanized Seed Corpora without Romanizations — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
- South Tyrolean Dialect-to-Standard Speech Translation: A Resource — 2026 · Proceedings of the First Workshop on Dialects in NLP –- A Resource Perspective
- Voices from the Margins: Modeling Linguistic Diversity in Spontaneous Speech for Low-Resource Languages — 2026 · Proceedings of the Ninth Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-9)
- A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation — 2025 · arXiv:2506.02894
- Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study — 2025 · Proceedings of the 12th Workshop on NLP for Similar Languages, Varieties and Dialects
- Indigenous Languages Spoken in Argentina: A Survey of NLP and Speech Resources — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
- Make Every Letter Count: Building Dialect Variation Dictionaries from Monolingual Corpora — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
- Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model — 2024 · arXiv:2402.07827
- Data Collection Pipeline for Low-Resource Languages: A Case Study on Constructing a Tetun Text Corpus — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Highly Granular Dialect Normalization and Phonological Dialect Translation for Limburgish — 2024 · Proceedings of the Eleventh Workshop on NLP for Similar Languages, Varieties, and Dialects (VarDial 2024)
- MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
- Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Voices Unheard: NLP Resources and Models for Yorùbá Regional Dialects — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
- What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- GlotLID: Language Identification for Low-Resource Languages — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Low-resource Bilingual Dialect Lexicon Induction with Large Language Models — 2023 · arXiv:2304.09957