Julen Etxaniz

Julen Etxaniz

Hizkuntzaren Azterketa eta Prozesamendua Doktoregoko ikaslea

Euskal Herriko Unibertsitatea (UPV/EHU)

Informatika Fakultatea

 Biografia

Hizkuntzaren Azterketa eta Prozesamendua Doktoregoko ikaslea Euskal Herriko Unibertsitateko (UPV/EHU) Informatika Fakultatean. Informatika Ingeniaritzan graduatua Software Ingeniaritza espezialitatearekin. Hizkuntzaren Azterketa eta Prozesamendua Masterra.

Web honetan informazio hau aurkituko duzu:  Trebetasunak,  Ziurtagiriak,  Proiektuak,  Etiketak eta  Kontaktua.

Interesak
  •  Programazioa
  •  Web Garapena
  •  Software Ingeniaritza
  •  Ikasketa Automatikoa
  •  Ikasketa Sakona
  •  Hizkuntzaren Prozesamendua
Ikasketak
  • Informatika Ingeniaritzako Gradua, 2017-2021

    Euskal Herriko Unibertsitatea (UPV/EHU)

  • Hizkuntzaren Azterketa eta Prozesamendua Masterra, 2021-2022

    Euskal Herriko Unibertsitatea (UPV/EHU)

  • Hizkuntzaren Azterketa eta Prozesamendua Doktoregoa, 2023-Gaur

    Euskal Herriko Unibertsitatea (UPV/EHU)

 Esperientzia

 
 
 
 
 
UPV/EHU
Hizkuntzaren Azterketa eta Prozesamendua Doktoregoko ikaslea
urtarrila 2023 – Gaur egun Donostia

 Ikasketak

 
 
 
 
 
UPV/EHU
Informatikan Ingeniaritzako Gradua
iraila 2017 – iraila 2021 Donostia
 
 
 
 
 
UPV/EHU
Hizkuntzaren Azterketa eta Prozesamendua Masterra
urria 2021 – urria 2021 Donostia
 
 
 
 
 
UPV/EHU
Hizkuntzaren Azterketa eta Prozesamendua Doktoregoa
urtarrila 2023 – Gaur egun Donostia

 Hizkuntzak

basque-country
Euskara
spain
Español
united-kingdom
English

 Programazio Lengoaiak

Python
R
Java
JavaScript
PHP
SQL

 Web Garapena

HTML5
CSS3
Bootstrap
hugo
Hugo
django
Django
dotnet
.NET

 Software Ingeniaritza

Betekizunak
Diseinua
Garapena
Probak
Metodologiak
Bertsio Kontrola

 Ikasketa Automatikoa

Klasifikazioa
Erregresioa
Sare Neuronalak
jupyter
Jupyter Notebook
scikit-learn
Scikit-Learn
tensorflow
Tensorflow

 Tresnak

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.

Proiektuak

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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

Zure erakuslehio digitala Sare Zerbitzuak eta Aplikazioak 2019-2020

Academic Webgunea

Academic Webgunea

Academic webgune pertsonala, atal hauek dituena: deskribapena, esteka sozialak, biografia, interesak, ikasketak, trebetasunak, esperientzia, lorpenak, proiektuak eta kontaktuko infomazioa.

Antxieta Arkeologi Taldea Webgunea

Antxieta Arkeologi Taldea Webgunea

Antxieta Arkeologi Taldearen webgunea, gipuzkoan ikerketa arkeologikoa garatzen duen irabazi asmorik gabeko talde kulturala.

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 Webgunea

GitHub Webgunea

GitHub webgune pertsonala, atal hauek dituena: argazkia, deskribapen motza, esteka sozialak eta GitHub-eko errepositorioak eta gaiak.

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

Galderen jokoa Web Sistemak 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

 Kontaktua