4 papers
SemiAdapt-Instruct: Extensible Instruction Tuning via Latent Domain-Specialised Adapters
Josh McGiff, Salma Mekaoui, Robert Shanahan +1
Instruction-tuned LLMs are deployed into environments where domains evolve, yet extending a fine-tuned model's capabilities without full retraining remains an unsolved practical ch…
Irish-BLiMP: A Linguistic Benchmark for Evaluating Human and Language Model Performance in a Low-Resource Setting
Josh McGiff, Khanh-Tung Tran, William Mulcahy +7
We present Irish-BLiMP (Irish Benchmark of Linguistic Minimal Pairs), the first dataset and framework designed for fine-grained evaluation of linguistic competence in the Irish lan…
SemiAdapt and SemiLoRA: Efficient Domain Adaptation for Transformer-based Low-Resource Language Translation with a Case Study on Irish
Josh McGiff, Nikola S. Nikolov
Fine-tuning is widely used to tailor large language models for specific tasks such as neural machine translation (NMT). However, leveraging transfer learning is computationally exp…
Overcoming Data Scarcity in Generative Language Modelling for Low-Resource Languages: A Systematic Review
Josh McGiff, Nikola S. Nikolov
Generative language modelling has surged in popularity with the emergence of services such as ChatGPT and Google Gemini. While these models have demonstrated transformative potenti…