67 citations · 261 across the 19 of their papers we have counts for
22 papers
Do Multilingual Language Models Think Better in English?
Julen Etxaniz, Gorka Azkune, Aitor Soroa +2
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 machin…
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Hugo Laurençon, Lucile Saulnier, Thomas Wang +51
As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop,…
Noisy Channel for Automatic Text Simplification
Oscar M Cumbicus-Pineda, Iker Gutiérrez-Fandiño, Itziar Gonzalez-Dios +1
In this paper we present a simple re-ranking method for Automatic Sentence Simplification based on the noisy channel scheme. Instead of directly computing the best simplification g…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Principled Paraphrase Generation with Parallel Corpora
Aitor Ormazabal, Mikel Artetxe, Aitor Soroa +2
Round-trip Machine Translation (MT) is a popular choice for paraphrase generation, which leverages readily available parallel corpora for supervision. In this paper, we formalize t…
PoeLM: A Meter- and Rhyme-Controllable Language Model for Unsupervised Poetry Generation
Aitor Ormazabal, Mikel Artetxe, Manex Agirrezabal +2
Formal verse poetry imposes strict constraints on the meter and rhyme scheme of poems. Most prior work on generating this type of poetry uses existing poems for supervision, which…
Does Corpus Quality Really Matter for Low-Resource Languages?
Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri +2
The vast majority of non-English corpora are derived from automatically filtered versions of CommonCrawl. While prior work has identified major issues on the quality of these datas…
Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources
Angelina McMillan-Major, Zaid Alyafeai, Stella Biderman +15
In recent years, large-scale data collection efforts have prioritized the amount of data collected in order to improve the modeling capabilities of large language models. This prio…
Image Captioning for Effective Use of Language Models in Knowledge-Based Visual Question Answering
Ander Salaberria, Gorka Azkune, Oier Lopez de Lacalle +2
Integrating outside knowledge for reasoning in visio-linguistic tasks such as visual question answering (VQA) is an open problem. Given that pretrained language models have been sh…
Inferring spatial relations from textual descriptions of images
Aitzol Elu, Gorka Azkune, Oier Lopez de Lacalle +3
Generating an image from its textual description requires both a certain level of language understanding and common sense knowledge about the spatial relations of the physical enti…
Beyond Offline Mapping: Learning Cross Lingual Word Embeddings through Context Anchoring
Aitor Ormazabal, Mikel Artetxe, Aitor Soroa +2
Recent research on cross-lingual word embeddings has been dominated by unsupervised mapping approaches that align monolingual embeddings. Such methods critically rely on those embe…
Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning
Jon Ander Campos, Kyunghyun Cho, Arantxa Otegi +3
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…
Spot The Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems
Jan Deriu, Don Tuggener, Pius von Däniken +6
The lack of time-efficient and reliable evaluation methods hamper the development of conversational dialogue systems (chatbots). Evaluations requiring humans to converse with chatb…
DoQA -- Accessing Domain-Specific FAQs via Conversational QA
Jon Ander Campos, Arantxa Otegi, Aitor Soroa +3
The goal of this work is to build conversational Question Answering (QA) interfaces for the large body of domain-specific information available in FAQ sites. We present DoQA, a dat…
Evaluating Multimodal Representations on Visual Semantic Textual Similarity
Oier Lopez de Lacalle, Ander Salaberria, Aitor Soroa +2
The combination of visual and textual representations has produced excellent results in tasks such as image captioning and visual question answering, but the inference capabilities…
Give your Text Representation Models some Love: the Case for Basque
Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos +4
Word embeddings and pre-trained language models allow to build rich representations of text and have enabled improvements across most NLP tasks. Unfortunately they are very expensi…
Analyzing the Limitations of Cross-lingual Word Embedding Mappings
Aitor Ormazabal, Mikel Artetxe, Gorka Labaka +2
Recent research in cross-lingual word embeddings has almost exclusively focused on offline methods, which independently train word embeddings in different languages and map them to…
Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset
Oier Lopez de Lacalle, Aitor Soroa, Eneko Agirre
In this paper we introduce vSTS, a new dataset for measuring textual similarity of sentences using multimodal information. The dataset is comprised by images along with its respect…
The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD
Eneko Agirre, Oier López de Lacalle, Aitor Soroa
UKB is an open source collection of programs for performing, among other tasks, knowledge-based Word Sense Disambiguation (WSD). Since it was released in 2009 it has been often use…
Bilingual Embeddings with Random Walks over Multilingual Wordnets
J. Goikoetxea, A. Soroa, E. Agirre
Bilingual word embeddings represent words of two languages in the same space, and allow to transfer knowledge from one language to the other without machine translation. The main a…
Improving distant supervision using inference learning
Roland Roller, Eneko Agirre, Aitor Soroa +1
Distant supervision is a widely applied approach to automatic training of relation extraction systems and has the advantage that it can generate large amounts of labelled data with…
Studying the Wikipedia Hyperlink Graph for Relatedness and Disambiguation
Eneko Agirre, Ander Barrena, Aitor Soroa
Hyperlinks and other relations in Wikipedia are a extraordinary resource which is still not fully understood. In this paper we study the different types of links in Wikipedia, and…