178 citations · 455 across the 19 of their papers we have counts for
23 papers
Should I try multiple optimizers when fine-tuning pre-trained Transformers for NLP tasks? Should I tune their hyperparameters?
Nefeli Gkouti, Prodromos Malakasiotis, Stavros Toumpis +1
NLP research has explored different neural model architectures and sizes, datasets, training objectives, and transfer learning techniques. However, the choice of optimizer during t…
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking
Lefteris Loukas, Ilias Stogiannidis, Odysseas Diamantopoulos +2
Standard Full-Data classifiers in NLP demand thousands of labeled examples, which is impractical in data-limited domains. Few-shot methods offer an alternative, utilizing contrasti…
Cache me if you Can: an Online Cost-aware Teacher-Student framework to Reduce the Calls to Large Language Models
Ilias Stogiannidis, Stavros Vassos, Prodromos Malakasiotis +1
Prompting Large Language Models (LLMs) performs impressively in zero- and few-shot settings. Hence, small and medium-sized enterprises (SMEs) that cannot afford the cost of creatin…
Breaking the Bank with ChatGPT: Few-Shot Text Classification for Finance
Lefteris Loukas, Ilias Stogiannidis, Prodromos Malakasiotis +1
We propose the use of conversational GPT models for easy and quick few-shot text classification in the financial domain using the Banking77 dataset. Our approach involves in-contex…
Legal-Tech Open Diaries: Lesson learned on how to develop and deploy light-weight models in the era of humongous Language Models
Stelios Maroudas, Sotiris Legkas, Prodromos Malakasiotis +1
In the era of billion-parameter-sized Language Models (LMs), start-ups have to follow trends and adapt their technology accordingly. Nonetheless, there are open challenges since th…
An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification
Ilias Chalkidis, Xiang Dai, Manos Fergadiotis +2
Non-hierarchical sparse attention Transformer-based models, such as Longformer and Big Bird, are popular approaches to working with long documents. There are clear benefits to thes…