9 citations · 14 across the 5 of their papers we have counts for
5 papers
SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures
Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27
We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…
Report-based Recommendations for Policy Making and Agency Operations: Dataset and LLM Evaluation
Aleksandra Edwards, Thomas Edwards, Jose Camacho-Collados +1
Large Language Models (LLMs) are extensively used in text generation tasks. These generative capabilities bring us to a point where LLMs could potentially provide useful insights i…
Language Models for Text Classification: Is In-Context Learning Enough?
Aleksandra Edwards, Jose Camacho-Collados
Recent foundational language models have shown state-of-the-art performance in many NLP tasks in zero- and few-shot settings. An advantage of these models over more standard approa…
Guiding Generative Language Models for Data Augmentation in Few-Shot Text Classification
Aleksandra Edwards, Asahi Ushio, Jose Camacho-Collados +2
Data augmentation techniques are widely used for enhancing the performance of machine learning models by tackling class imbalance issues and data sparsity. State-of-the-art generat…
Predicting Themes within Complex Unstructured Texts: A Case Study on Safeguarding Reports
Aleksandra Edwards, David Rogers, Jose Camacho-Collados +2
The task of text and sentence classification is associated with the need for large amounts of labelled training data. The acquisition of high volumes of labelled datasets can be ex…