{"total":18,"rows":[{"id":"2205.06266","title":"Lifting the Curse of Multilinguality by Pre-training Modular Transformers","created":"2022-05-12","cited_by_count":146,"area":null},{"id":"2106.15115","title":"Neural Machine Translation for Low-Resource Languages: A Survey","created":"2021-06-29","cited_by_count":109,"area":null},{"id":"2210.07700","title":"Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey","created":"2022-10-14","cited_by_count":80,"area":null},{"id":"2103.06799","title":"Towards Continual Learning for Multilingual Machine Translation via Vocabulary Substitution","created":"2021-03-11","cited_by_count":31,"area":null},{"id":"2212.10503","title":"Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training","created":"2022-12-20","cited_by_count":24,"area":null},{"id":"2305.14224","title":"mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations","created":"2023-05-23","cited_by_count":24,"area":null},{"id":"2106.06797","title":"Machine Translation into Low-resource Language Varieties","created":"2021-06-12","cited_by_count":19,"area":null},{"id":"2103.10531","title":"Improving the Lexical Ability of Pretrained Language Models for Unsupervised Neural Machine Translation","created":"2021-03-18","cited_by_count":14,"area":null},{"id":"2209.15236","title":"Language-Family Adapters for Low-Resource Multilingual Neural Machine Translation","created":"2022-09-30","cited_by_count":14,"area":null},{"id":"2109.04556","title":"Subword Mapping and Anchoring across Languages","created":"2021-09-09","cited_by_count":12,"area":null},{"id":"2202.12312","title":"Oolong: Investigating What Makes Transfer Learning Hard with Controlled Studies","created":"2022-02-24","cited_by_count":9,"area":null},{"id":"2109.11177","title":"Exploiting Curriculum Learning in Unsupervised Neural Machine Translation","created":"2021-09-23","cited_by_count":6,"area":null},{"id":"2208.12097","title":"Training a T5 Using Lab-sized Resources","created":"2022-08-25","cited_by_count":5,"area":null},{"id":"2104.05848","title":"Family of Origin and Family of Choice: Massively Parallel Lexiconized Iterative Pretraining for Severely Low Resource Machine Translation","created":"2021-04-12","cited_by_count":4,"area":null},{"id":"2106.04995","title":"Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study","created":"2021-06-09","cited_by_count":3,"area":null},{"id":"2510.07613","title":"Vocabulary embeddings organize linguistic structure early in language model training","created":"2025-10-08","cited_by_count":2,"area":null},{"id":"2211.07534","title":"High-Resource Methodological Bias in Low-Resource Investigations","created":"2022-11-14","cited_by_count":1,"area":null},{"id":"2603.17087","title":"Ensemble Self-Training for Unsupervised Machine Translation","created":"2026-03-17","cited_by_count":0,"area":null}],"next_cursor":null}