activity
20212023
most citedKUCST@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2023

KUCST at CheckThat 2023: How good can we be with a generic model?

Manex Agirrezabal

In this paper we present our method for tasks 2 and 3A at the CheckThat2023 shared task. We make use of a generic approach that has been used to tackle a diverse set of tasks, insp…

cs.CL20221 cited

KUCST@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text

Manex Agirrezabal, Janek Amann

In this paper we present our approach for detecting signs of depression from social media text. Our model relies on word unigrams, part-of-speech tags, readabilitiy measures and th…

cs.NE20221 cited

Fashion Style Generation: Evolutionary Search with Gaussian Mixture Models in the Latent Space

Imke Grabe, Jichen Zhu, Manex Agirrezabal

This paper presents a novel approach for guiding a Generative Adversarial Network trained on the FashionGen dataset to generate designs corresponding to target fashion styles. Find…

cs.CL2022

From meaning to perception -- exploring the space between word and odor perception embeddings

Janek Amann, Manex Agirrezabal

In this paper we propose the use of the Word2vec algorithm in order to obtain odor perception embeddings (or smell embeddings), only using publicly available perfume descriptions.…

cs.CY2021

The Flipped Classroom model for teaching Conditional Random Fields in an NLP course

Manex Agirrezabal

In this article, we show and discuss our experience in applying the flipped classroom method for teaching Conditional Random Fields in a Natural Language Processing course. We pres…