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LoResMT 2026 — accepted papers

LoResMT 2026 is the 2026 edition of the Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT), held in Rabat, Morocco, March 2026 (publisher: Association for Computational Linguistics). The ACL Anthology lists 24 papers of it; our library holds 15 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Rabat, Morocco · 🗓 March 2026

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

  1. Are Small Language Models the Silver Bullet to Low-Resource Languages Machine Translation?Yewei Song, Lujun Li, Cedric Lothritz et al.1 citation · our summary
  2. Building and Evaluating a High Quality Parallel Corpus for English Urdu Low Resource Machine TranslationMunief Hassan Tahir, Hunain Azam, Sana Shams et al.1 citation · our summary
  3. Can LLMs Translate Italy's Language Varieties?Edoardo Signoroni, Pavel Rychlý1 citation · our summary
  4. Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAGDavid Samuel Setiawan, Raphaël Merx, Jey Han Lau1 citation · our summary
  5. Improving Indigenous Language Machine Translation with Synthetic Data and Language-Specific Preprocessing ↗Aashish Dhawan, Christopher Driggers-Ellis, Christan Grant et al.1 citation
  6. Tao–Filipino Neural Machine Translation: Strategies for Ultra–Low-Resource SettingsAdrian Denzel Macayan, Luis Andrew Sunga Madridijo, Ellexandrei Esponilla et al.1 citation · our summary

All accepted papers (24)

The most cited first; 15 with our summary link to their page here, the others to the original.

  1. Are Small Language Models the Silver Bullet to Low-Resource Languages Machine Translation?Yewei Song, Lujun Li, Cedric Lothritz et al.1 citation · our summary
  2. Building and Evaluating a High Quality Parallel Corpus for English Urdu Low Resource Machine TranslationMunief Hassan Tahir, Hunain Azam, Sana Shams et al.1 citation · our summary
  3. Can LLMs Translate Italy's Language Varieties?Edoardo Signoroni, Pavel Rychlý1 citation · our summary
  4. Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAGDavid Samuel Setiawan, Raphaël Merx, Jey Han Lau1 citation · our summary
  5. Improving Indigenous Language Machine Translation with Synthetic Data and Language-Specific Preprocessing ↗Aashish Dhawan, Christopher Driggers-Ellis, Christan Grant et al.1 citation
  6. Tao–Filipino Neural Machine Translation: Strategies for Ultra–Low-Resource SettingsAdrian Denzel Macayan, Luis Andrew Sunga Madridijo, Ellexandrei Esponilla et al.1 citation · our summary
  7. Assessing and Improving Punctuation Robustness in English-Marathi Machine TranslationKaustubh Shivshankar Shejole, Sourabh Deoghare, Pushpak Bhattacharyyaour summary
  8. Can Linguistically Related Languages Guide LLM Translation in Low-Resource Settings?Aishwarya Ramasethu, Rohin Garg, Niyathi Allu et al.our summary

 Papers with our summary in our library (15)

The most cited first (OpenAlex citations plus our library's).

  1. Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAGDavid Samuel Setiawan, Raphaël Merx, Jey Han Lau2026 · 1 citation

 Top topics

Topics of its works in our library, with the number of works on each.

Machine translation (12)Low-resource languages (12)English (3)Evaluation & benchmarks (2)Language models & pretraining (1)Hebrew & Aramaic (1)Biblical Hebrew (1)

 Fields

Arts and Humanities (15)Computer Science (15)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

 Top institutions

Institutions on the bylines of its works here, by the number of works.

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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