Search Results for author:
Found 6 papers, 3 papers with code
Understanding Transformers for Bot Detection in Twitter
In this paper we shed light on the impact of fine-tuning over social media data in the internal representations of neural language models.
On the Impact of Knowledge-based Linguistic Annotations in the Quality of Scientific Embeddings
In essence, embedding algorithms work by optimizing the distance between a word and its usual context in order to generate an embedding space that encodes the distributional representation of words.
European Language Grid: A Joint Platform for the European Language Technology Community
Europe is a multilingual society, in which dozens of languages are spoken.
Classifying Scientific Publications with BERT -- Is Self-Attention a Feature Selection Method?
We compare and evaluate the subset of the most attended words with feature selection methods normally used for text classification in order to characterize self-attention as a possible feature selection approach.
An Empirical Study on Pre-trained Embeddings and Language Models for Bot Detection
Fine-tuning pre-trained language models has significantly advanced the state of art in a wide range of NLP downstream tasks.
Enabling FAIR Research in Earth Science through Research Objects
Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse.
