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Gorka Azkune

7 accepted papers

2025

EnerGIZAr: Leveraging GIZA++ for Effective Tokenizer Initialization

ACL 2025finding

Continual pre-training has long been considered the default strategy for adapting models to non-English languages, but struggles with initializing new embeddings, particularly for non-Latin scripts. In this work, we propose EnerGIZAr, a novel methodology that improves continual pre-training by lever…

2025

Improving the Efficiency of Visually Augmented Language Models

COLING 2025main

Despite the impressive performance of autoregressive Language Models (LM) it has been shown that due to reporting bias, LMs lack visual knowledge, i.e. they do not know much about the visual world and its properties. To augment LMs with visual knowledge, existing solutions often rely on explicit ima…

2025

Vision-Language Models Struggle to Align Entities across Modalities

ACL 2025finding

Cross-modal entity linking refers to the ability to align entities and their attributes across different modalities. While cross-modal entity linking is a fundamental skill needed for real-world applications such as multimodal code generation, fake news detection, or scene understanding, it has not…

2024

BertaQA: How Much Do Language Models Know About Local Culture?

NeurIPS 2024poster

Large Language Models (LLMs) exhibit extensive knowledge about the world, but most evaluations have been limited to global or anglocentric subjects. This raises the question of how well these models perform on topics relevant to other cultures, whose presence on the web is not that prominent. To add…

2024

BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval

NeurIPS 2024poster

Existing Vision-Language Compositionality (VLC) benchmarks like SugarCrepe are formulated as image-to-text retrieval problems, where, given an image, the models need to select between the correct textual description and a synthetic hard negative text. In this work, we present the Bidirectional Visio…

2024

Do Multilingual Language Models Think Better in English?

NAACL 2024short

Translate-test is a popular technique to improve the performance of multilingual language models. This approach works by translating the input into English using an external machine translation system before running inference. However, these improvements can be attributed to the use of a separate tr…

2020

Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning

COLING 2020main

The interaction of conversational systems with users poses an exciting opportunity for improving them after deployment, but little evidence has been provided of its feasibility. In most applications, users are not able to provide the correct answer to the system, but they are able to provide binary…