Gloss-to-Text Translation for Libras and Portuguese: Evaluating Pretrained and Fine-Tuned Encoder-Decoder Models

Instruction-Tuned Large Language Models for Mexican Sign Language Gloss Translation with Linguistic and Synthetic Data Augmentation

Referenceless Evaluation of Machine Translation Models by Ranking Performance in Romanian to English Translate-train Settings

Data-Efficient Adaptation of Multilingual LLMs to Ukrainian

This work combines vocabulary surgery for tokenizer adaptation without full retraining, cross-lingual transfer of quality classifiers via translation, enabling filtering without target-language annotations, and generation of instruction data through translation, task conversion, and targeted synthesis.

LoRA Fine-Tuning, Frontier-LLM Prompting, and Encoder-Decoder Baselines for Low-Resource Bidirectional Sign Language Gloss Translation

Benchmarking Open-Source Vietnamese-English Speech-to-Text Translation Systems

Speech-to-text translation for low-resource language pairs such as Vietnamese–English remains underexplored, despite growing demand in real-world applications. In this study, we present a systematic zero-shot benchmark on the Vietnamese test split of FLEURS, evaluating 30 configurations across three system families: co...

Controllable Sentence Simplification in Italian: Fine-Tuning Large Language Models on Automatically Generated Resources

Results from automatic and human evaluations show that fine-tuning on IMPaCTS improves performance both in terms of task completion and adherence to the targeted readability levels compared to few-shot baselines.