--- title: "Low-resource languages — papers, page 3" description: "Low-resource languages: 153 papers of the Elamur Research library · page 3 of 3 · 126–153, the most cited first." canonical: "https://research.elamur.ai/free/en/topics/low-resource-languages/page/3/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/low-resource-languages/page/3/) [home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Low-resource languages](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) / page 3 # 🌱 Low-resource languages 153 papers · page 3 of 3 · 126–153 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/) Languages with little data: endangered, indigenous and under-served languages and how to work with them. [← prev](https://md.research.elamur.ai/free/en/topics/low-resource-languages/page/2/) [1](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) [2](https://md.research.elamur.ai/free/en/topics/low-resource-languages/page/2/) **3** 126. [**Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages**Noam Dahan, Omer Kidron, Gabriel Stanovsky*2026*](https://md.research.elamur.ai/free/en/papers/dahan-2026-leveraging-digitized-newspapers-collect-summarization/) 127. [**LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2026*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2026-lgse-lexically-grounded-subword-embedding/) 128. [**LV-ROVER-MLT: Low-Resource Maltese OCR by Synthetic Fine-Tuning and Multi-Stream Arbitration**Adam Darmanin*2026*](https://md.research.elamur.ai/free/en/papers/darmanin-2026-lv-rover-mlt-low-resource/) 129. [**MaskedVerbalizer: Automatic Verbalizer Construction for Few-Shot Text Classification in Low-Resource Right-to-Left Languages**Faizad Ullah, Furqan Sikandar, Areeba Waqar, et al.*2026*](https://md.research.elamur.ai/free/en/papers/ullah-2026-maskedverbalizer-automatic-verbalizer-construction-few/) 130. [**Morphological Parsing for Media Lengua: When Accessibility Matters More Than State-of-the-Art**Jesse Stewart, Olga Kriukova*2026*](https://md.research.elamur.ai/free/en/papers/stewart-2026-morphological-parsing-media-lengua-when/) 131. [**Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs**Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury*2026*](https://md.research.elamur.ai/free/en/papers/bhatti-2026-multi-task-instruction-tuning-data/) 132. [**Nepali Lemmatization with Multilingual Transformers: Intrinsic and Extrinsic Evaluation in a Low-Resource Setting**Sunil Regmi, Sundeep Dawadi, Bal Krishna Bal*2026*](https://md.research.elamur.ai/free/en/papers/regmi-2026-nepali-lemmatization-multilingual-transformers-intrinsic/) 133. [**On the Robustness of Morphosyntactic Transformation with Large Language Models: The Case of Quechua Collao**Pool Pocco, Arturo Oncevay*2026*](https://md.research.elamur.ai/free/en/papers/pocco-2026-robustness-morphosyntactic-transformation-large-language/) 134. [**Parsing Nheengatu: Performance Gains for a Brazilian Indigenous Universal Dependencies Treebank**Dominick Maia Alexandre, Leonel Figueiredo de Alencar*2026*](https://md.research.elamur.ai/free/en/papers/alexandre-2026-parsing-nheengatu-performance-gains-brazilian/) 135. [**Phonetic-based Ranking for Improved Pseudo-Labeling in Low-Resource ASR**Marco Matassoni, Roberto Gretter, Falavigna Daniele, et al.*2026*](https://md.research.elamur.ai/free/en/papers/matassoni-2026-phonetic-based-ranking-improved-pseudo/) 136. [**Quality and Appropriateness of Large Text Datasets for Irish NLP**Abigail Walsh, Mark Andrade, Jane Lauren Adkins, et al.*2026*](https://md.research.elamur.ai/free/en/papers/walsh-2026-quality-appropriateness-large-text-datasets/) 137. [**SAINT: Multilingual Span-Level Interpretability for Sentiment Analysis**Seid Muhie Yimam, Tadesse Destaw Belay, Robert Geislinger, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yimam-2026-saint-multilingual-span-level-interpretability/) 138. [**Same-Language Subtitles for Low-resource Languages: A Case of Bundelkhandi**Anirudh Pradhan, Ayushi Pandey, Divyansh Kushwaha, et al.*2026*](https://md.research.elamur.ai/free/en/papers/pradhan-2026-same-language-subtitles-low-resource/) 139. [**Script Correction and Synthetic Pivoting: Adapting Tencent HY-MT for Low-Resource Turkic Translation**Bolgov Maxim*2026*](https://md.research.elamur.ai/free/en/papers/maxim-2026-script-correction-synthetic-pivoting-adapting/) 140. [**SemiAdapt: Semi-Supervised and Efficient LoRA-Based Domain Adaptation for Low-Resource Irish Machine Translation with Transformers**Josh Mcgiff, Nikola S. Nikolov*2026*](https://md.research.elamur.ai/free/en/papers/mcgiff-2026-semiadapt-semi-supervised-efficient-lora/) 141. [**Small Language Models for Less-Resourced Languages in a Real-World Scenario: The Case for Catalan**Roser Saurí, Josep Sànchez-Ferreres, Lluis Padro, et al.*2026*](https://md.research.elamur.ai/free/en/papers/sauri-2026-small-language-models-less-resourced/) 142. [**Synthetic Instruction Generation for Low-Resource Nordic Languages: Viability and Limitations in LLM Instruction-Tuning**Mathias Stenlund, Annika Simonsen, Lars Bungum, et al.*2026*](https://md.research.elamur.ai/free/en/papers/stenlund-2026-synthetic-instruction-generation-low-resource/) 143. [**Task-Lens: Cross-Task Utility Based Speech Dataset Profiling for Low-Resource Indian Languages**Swati Sharma, Divya V. Sharma, Anubha Gupta*2026*](https://md.research.elamur.ai/free/en/papers/sharma-2026-task-lens-cross-task-utility/) 144. [**TG-ASR: Translation-Guided Learning with Parallel Gated Cross Attention for Low-Resource Automatic Speech Recognition**ChengYeh Yang, Chien-Chun Wang, Li-Wei Chen, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yang-2026-tg-asr-translation-guided-learning/) 145. [**Transfer Learning for Creole TTS: A Pilot Study on Whether Substrate Phonologies or Lexifier Vocabularies Matter More**Emmett Strickland, Marc Evrard, Valentina Fedchenko*2026*](https://md.research.elamur.ai/free/en/papers/strickland-2026-transfer-learning-creole-tts-pilot/) 146. [**Trustworthy NLP for Low-Resource Languages: Agent-Based Uncertainty Modeling for Hebrew Radiology Report Structuring**Hadas Ben Atya, Naama Gavrielov, Zvi Badash, et al.*2026*](https://md.research.elamur.ai/free/en/papers/atya-2026-trustworthy-nlp-low-resource-languages/) 147. [**Voice Activation Detection for Transcription of Indigenous Languages**Rolando Coto-Solano, Mikaela Browning, Thomas Corrado, et al.*2026*](https://md.research.elamur.ai/free/en/papers/solano-2026-voice-activation-detection-transcription-indigenous/) 148. [**Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation**Shenbin Qian, Yves Scherrer*2026*](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) 149. [**AI-Driven Generation of Old English: A Framework for Low-Resource Languages**Rodrigo Gabriel Salazar Alva, Matias Nunez, Cristian Lopez, et al.*2025*](https://md.research.elamur.ai/free/en/papers/alva-2025-ai-driven-generation-old-english/) 150. [**Evaluating the Performance of Transformers in Translating Low-Resource Languages through Akkadian**Daniel A. Jones, Ruslan Mitkov*2025*](https://md.research.elamur.ai/free/en/papers/jones-2025-evaluating-performance-transformers-translating-low/) 151. [**Hybrid Deep Learning and Signal Processing for Arabic Dialect Recognition in Low-Resource Settings**Ghazal Al-Shwayyat, Omer Nezih Gerek*2025*](https://md.research.elamur.ai/free/en/papers/al-shwayyat-2025-hybrid-deep-learning-signal-processing/) 152. [**Poem Meter Classification of Recited Arabic Poetry: Integrating High-Resource Systems for a Low-Resource Task**Maged S. Al-Shaibani, Zaid Alyafeai, Irfan Ahmad*2025*](https://md.research.elamur.ai/free/en/papers/al-shaibani-2025-poem-meter-classification-recited-arabic/) 153. [**NoLoR: An ASR-Based Framework for Expedited Endangered Language Documentation with Neo-Aramaic as a Case Study**Matthew Nazari*2024*](https://md.research.elamur.ai/free/en/papers/nazari-2024-nolor-asr-based-framework-expedited/) [← prev](https://md.research.elamur.ai/free/en/topics/low-resource-languages/page/2/) [1](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) [2](https://md.research.elamur.ai/free/en/topics/low-resource-languages/page/2/) **3**