61 citations · 152 across the 21 of their papers we have counts for
21 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…
Multilingual Topic Classification in X: Dataset and Analysis
Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri +1
In the dynamic realm of social media, diverse topics are discussed daily, transcending linguistic boundaries. However, the complexities of understanding and categorising this conte…
A Systematic Analysis on the Temporal Generalization of Language Models in Social Media
Asahi Ushio, Jose Camacho-Collados
In machine learning, temporal shifts occur when there are differences between training and test splits in terms of time. For streaming data such as news or social media, models are…
DANSK and DaCy 2.6.0: Domain Generalization of Danish Named Entity Recognition
Kenneth Enevoldsen, Emil Trenckner Jessen, Rebekah Baglini
Named entity recognition is one of the cornerstones of Danish NLP, essential for language technology applications within both industry and research. However, Danish NER is inhibite…
SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research
Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri +5
Despite its relevance, the maturity of NLP for social media pales in comparison with general-purpose models, metrics and benchmarks. This fragmented landscape makes it hard for the…
RelBERT: Embedding Relations with Language Models
Asahi Ushio, Jose Camacho-Collados, Steven Schockaert
Many applications need access to background knowledge about how different concepts and entities are related. Although Knowledge Graphs (KG) and Large Language Models (LLM) can addr…
A Practical Toolkit for Multilingual Question and Answer Generation
Asahi Ushio, Fernando Alva-Manchego, Jose Camacho-Collados
Generating questions along with associated answers from a text has applications in several domains, such as creating reading comprehension tests for students, or improving document…
An Empirical Comparison of LM-based Question and Answer Generation Methods
Asahi Ushio, Fernando Alva-Manchego, Jose Camacho-Collados
Question and answer generation (QAG) consists of generating a set of question-answer pairs given a context (e.g. a paragraph). This task has a variety of applications, such as data…
An Efficient Multilingual Language Model Compression through Vocabulary Trimming
Asahi Ushio, Yi Zhou, Jose Camacho-Collados
Multilingual language model (LM) have become a powerful tool in NLP especially for non-English languages. Nevertheless, model parameters of multilingual LMs remain large due to the…
A RelEntLess Benchmark for Modelling Graded Relations between Named Entities
Asahi Ushio, Jose Camacho Collados, Steven Schockaert
Relations such as "is influenced by", "is known for" or "is a competitor of" are inherently graded: we can rank entity pairs based on how well they satisfy these relations, but it…
Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shifts
Asahi Ushio, Leonardo Neves, Vitor Silva +2
Recent progress in language model pre-training has led to important improvements in Named Entity Recognition (NER). Nonetheless, this progress has been mainly tested in well-format…
Generative Language Models for Paragraph-Level Question Generation
Asahi Ushio, Fernando Alva-Manchego, Jose Camacho-Collados
Powerful generative models have led to recent progress in question generation (QG). However, it is difficult to measure advances in QG research since there are no standardized reso…
Twitter Topic Classification
Dimosthenis Antypas, Asahi Ushio, Jose Camacho-Collados +3
Social media platforms host discussions about a wide variety of topics that arise everyday. Making sense of all the content and organising it into categories is an arduous task. A…
T-NER: An All-Round Python Library for Transformer-based Named Entity Recognition
Asahi Ushio, Jose Camacho-Collados
Language model (LM) pretraining has led to consistent improvements in many NLP downstream tasks, including named entity recognition (NER). In this paper, we present T-NER (Transfor…
TweetNLP: Cutting-Edge Natural Language Processing for Social Media
Jose Camacho-Collados, Kiamehr Rezaee, Talayeh Riahi +11
In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic foc…
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…
Distilling Relation Embeddings from Pre-trained Language Models
Asahi Ushio, Jose Camacho-Collados, Steven Schockaert
Pre-trained language models have been found to capture a surprisingly rich amount of lexical knowledge, ranging from commonsense properties of everyday concepts to detailed factual…
BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Identify Analogies?
Asahi Ushio, Luis Espinosa-Anke, Steven Schockaert +1
Analogies play a central role in human commonsense reasoning. The ability to recognize analogies such as "eye is to seeing what ear is to hearing", sometimes referred to as analogi…
Back to the Basics: A Quantitative Analysis of Statistical and Graph-Based Term Weighting Schemes for Keyword Extraction
Asahi Ushio, Federico Liberatore, Jose Camacho-Collados
Term weighting schemes are widely used in Natural Language Processing and Information Retrieval. In particular, term weighting is the basis for keyword extraction. However, there a…
Latent Space Cartography: Generalised Metric-Inspired Measures and Measure-Based Transformations for Generative Models
Max F. Frenzel, Bogdan Teleaga, Asahi Ushio
Deep generative models are universal tools for learning data distributions on high dimensional data spaces via a mapping to lower dimensional latent spaces. We provide a study of l…
Volatility Forecasts Using Nonlinear Leverage Effects
Kenichiro McAlinn, Asahi Ushio, Teruo Nakatsuma
The leverage effect-- the correlation between an asset's return and its volatility-- has played a key role in forecasting and understanding volatility and risk. While it is a long…