Julen Etxaniz

Julen Etxaniz

Estudiante de Doctorado en Análisis y Procesamiento del Lenguaje

Universidad del País Vasco (UPV/EHU)

Facultad de Informática

Estudiante de Doctorado en Análisis y Procesamiento del Lenguaje en la Facultad de Informática de la Universidad del País Vasco (UPV/EHU). Graduado en Ingeniería Informática con especialidad en Ingeniería del Software. Máster en Análisis y Procesamiento del Lenguaje.

En esta web encontrarás información sobre  Habilidades,  Certificados,  Proyectos,  Etiquetas y  Contacto.

 Experiencia

 
 
 
 
 
UPV/EHU
Doctorado en Análisis y Procesamiento del Lenguaje
enero 2023 – Actualmente Donostia

 Educación

 
 
 
 
 
UPV/EHU
Grado en Ingeniería Informática
septiembre 2017 – septiembre 2021 Donostia
 
 
 
 
 
UPV/EHU
Máster en Análisis y Procesamiento del Lenguaje
octubre 2021 – octubre 2021 Donostia
 
 
 
 
 
UPV/EHU
Doctorado en Análisis y Procesamiento del Lenguaje
enero 2023 – Actualmente Donostia

 Idiomas

basque-country
Euskara
spain
Español
united-kingdom
English

 Lenguajes de Programación

Python
R
Java
JavaScript
PHP
SQL

 Desarrollo Web

HTML5
CSS3
Bootstrap
hugo
Hugo
django
Django
dotnet
.NET

 Ingeniería del Software

Requerimientos
Diseño
Desarrollo
Pruebas
Metodologías
Control de Versiones

 Aprendizaje Automático

Clasificación
Regresión
Redes Neuronales
jupyter
Jupyter Notebook
scikit-learn
Scikit-Learn
tensorflow
Tensorflow

 Tools

Git
GitHub
xamarin
Xamarin
eclipse
Eclipse
visual-studio-code
Visual Studio Code
visual-studio
Visual Studio
Grounding Language Models for Compositional and Spatial Reasoning
Grounding Language Models for Compositional and Spatial Reasoning

Humans can learn to understand and process the distribution of space, and one of the initial tasks of Artificial Intelligence has been to show machines the relationships between space and the objects that appear in it. Humans naturally combine vision and textual information to acquire compositional and spatial relationships among objects, and when reading a text, we are able to mentally depict the spatial relationships that may appear in it. Thus, the visual differences between images depicting “a person sits and a dog stands” and “a person stands and a dog sits” are obvious for humans, but still not clear for automatic systems. In this project, we propose to evaluate grounded Neural Language models that can perform compositional and spatial reasoning. Neural Language models (LM) have shown impressive capabilities on many NLP tasks but, despite their success, they have been criticized for their lack of meaning. Vision-and-Language models (VLM), trained jointly on text and image data, have been offered as a response to such criticisms, but recent work has shown that these models struggle to ground spatial concepts properly. In the project, we evaluate state-of-the-art pre-trained and fine-tuned VLMs to understand their grounding level on compositional and spatial reasoning. We also propose a variety of methods to create synthetic datasets specially focused on compositional reasoning. We managed to accomplish all the objectives of this work. First, we improved the state-of-the-art in compositional reasoning. Next, we performed some zero-shot experiments on spatial reasoning. Finally, we explored three alternatives for synthetic dataset creation: text-to-image generation, image captioning and image retrieval. Code is released at https://github.com/juletx/spatial-reasoning and models are released at https://huggingface.co/juletxara.

Proyectos

*
Image Caption Generation

Image Caption Generation

Automatic Image Caption Generation model that uses a CNN to condition a LSTM based language model.

Shape Classification

Shape Classification

The goal of the project is to compare different classification algorithms on the solution of plane and car shape datasets.

100Iragarki

100Iragarki

Tu escaparate digital Servicios y Aplicaciones de Red 2019-2020

Academic Web

Academic Web

Web personal Academic que incluye una descripción corta, enlaces sociales, biografía, intereses, educación, habilidades, experiencia, logros, proyectos e información de contacto.

Antxieta Arkeologi Taldea Web

Antxieta Arkeologi Taldea Web

Web de Antxieta Arkeologi Taldea, grupo cultural sin ánimo de lucro que desarrolla la investigación arqueológica en Gipuzkoa.

BattleshipFeatureIDE

BattleshipFeatureIDE

Java Battleship FeatureIDE Software Product Line.

Community Detection

Community Detection

NIPS kongresuko autoreen komunitateak detektatzen metaheuristikoak erabiliz.

Comparing Writing Systems

Comparing Writing Systems

Comparing Writing Systems with Multilingual Grapheme-to-Phoneme and Phoneme-to-Grapheme Conversion.

Computational Syntax

Computational Syntax

Computational Syntax slides and exercises.

Corpus Linguistics

Corpus Linguistics

Corpus Linguistics slides, labs, assignments and data.

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing slides, labs and assignments.

Dialbot

Dialbot

Ikasketa sakonean oinarritutako muturretik muturrerako solasaldi sistema.

Egunean Behin Visual Question Answering Dataset

Egunean Behin Visual Question Answering Dataset

This is a Visual Question Answering dataset based on questions from the game Egunean Behin. Egunean Behin is a popular Basque quiz game. The game consists on answering 10 daily multiple choice questions.

GitHub Web

GitHub Web

Web personal GitHub que incluye una foto, descripción corta, enlaces sociales y repositorios y temas de GitHub.

Grounding Language Models for Spatial Reasoning

Grounding Language Models for Spatial Reasoning

Grounding Language Models for Spatial Reasoning

HackerRank Challenge Solutions

HackerRank Challenge Solutions

Solutions for programming challenges in multiple languages.

Hyperpartisan News Analysis With Scattertext

Hyperpartisan News Analysis With Scattertext

Hyperpartisan News Analysis With Scattertext

Machine Learning and Neural Networks labs

Machine Learning and Neural Networks labs

Machine Learning and Neural Networks labs.

Machine Learning and Neural Networks lectures

Machine Learning and Neural Networks lectures

Machine Learning and Neural Networks lectures.

Machine Learning exercises with R

Machine Learning exercises with R

Machine Learning exercises with R.

Mejorando la seguridad de mi web

Mejorando la seguridad de mi web

Analizaré mi web con herramientas como Hardenize y Security Headers para detectar los aspectos de seguridad que se pueden mejorar.

MFDS

MFDS

Métodos Formales de Desarrollo de Software.

NLP Applications I - Text Classification, Sequence Labelling, Opinion Mining and Question Answering

NLP Applications I - Text Classification, Sequence Labelling, Opinion Mining and Question Answering

NLP Applications I - Text Classification, Sequence Labelling, Opinion Mining and Question Answering slides, labs and project.

NLP Applications II - Information Extraction, Question Answering, Recommender Systems and Conversational Systems

NLP Applications II - Information Extraction, Question Answering, Recommender Systems and Conversational Systems

NLP Applications II - Information Extraction, Question Answering, Recommender Systems and Conversational Systems slides, labs and project.

ProMeta

ProMeta

Metaereduetan oinarritutako softwarearen garapenerako prozesuen definizio eta ezarpenerako sistema.

ProMeta IO-System

ProMeta IO-System

ProMeta proiektua IO-System.

ProMeta ModelEditor

ProMeta ModelEditor

ProMeta proiektua ModelEditor.

Quiz

Quiz

Juego de preguntas Sistemas Web 2019-2020

Spiking Neural Network

Spiking Neural Network

Simulating the Izhikevich spiking neuron model using the Brian2 software

Twitter Sentiment and Emotion Analysis

Twitter Sentiment and Emotion Analysis

Twitter Sentiment and Emotion Analysis.

Zero-shot and Translation Experiments on XQuAD, MLQA and TyDiQA

Zero-shot and Translation Experiments on XQuAD, MLQA and TyDiQA

Zero-shot and Translation Experiments on XQuAD, MLQA and TyDiQA

 Contacto