2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
High-quality Data-to-Text Generation for Severely Under-Resourced Languages with Out-of-the-box Large Language Models
Michela Lorandi, Anya Belz
The performance of NLP methods for severely under-resourced languages cannot currently hope to match the state of the art in NLP methods for well resourced languages. We explore th…
cs.CL2024
Assessing the Portability of Parameter Matrices Trained by Parameter-Efficient Finetuning Methods
Mohammed Sabry, Anya Belz
As the cost of training ever larger language models has grown, so has the interest in reusing previously learnt knowledge. Transfer learning methods have shown how reusing non-task…
cs.CL2023★ 2 cited
Data-to-text Generation for Severely Under-Resourced Languages with GPT-3.5: A Bit of Help Needed from Google Translate
Michela Lorandi, Anya Belz
LLMs like GPT are great at tasks involving English which dominates in their training data. In this paper, we look at how they cope with tasks involving languages that are severely…