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Despite Portuguese being one of the most spoken languages in the world, there is a lack of high-quality information retrieval datasets in that language. We present Quati, a dataset specifically designed for the Brazilian Portuguese…

Information Retrieval · Computer Science 2024-04-11 Mirelle Bueno , Eduardo Seiti de Oliveira , Rodrigo Nogueira , Roberto A. Lotufo , Jayr Alencar Pereira

This paper presents a monolingual BERT model for Galician. We follow the recent trend that shows that it is feasible to build robust monolingual BERT models even for relatively low-resource languages, while performing better than the…

Computation and Language · Computer Science 2021-04-08 David Vilares , Marcos Garcia , Carlos Gómez-Rodríguez

Generative Pre-trained Transformer (GPT) models have achieved remarkable performance on various natural language processing tasks, and have shown great potential as backbones for audio-and-text large language models (LLMs). Previous…

Definition modelling (DM) is the task of automatically generating a dictionary definition for a specific word. Computational systems that are capable of DM can have numerous applications benefiting a wide range of audiences. As DM is…

Computation and Language · Computer Science 2024-03-29 Anna Beatriz Dimas Furtado , Tharindu Ranasinghe , Frédéric Blain , Ruslan Mitkov

This study presents the design and development of the 21st Century Teacher Educator for Ghana GPT, a customized Generative AI (GenAI) tool created using OpenAI's Retrieval-Augmented Generation (RAG) and Interactive Semi-Automated Prompting…

Computers and Society · Computer Science 2025-04-11 Matthew Nyaaba

Transformer, based on the encoder-decoder framework, has achieved state-of-the-art performance on several natural language generation tasks. The encoder maps the words in the input sentence into a sequence of hidden states, which are then…

Computation and Language · Computer Science 2020-02-25 Rongxiang Weng , Haoran Wei , Shujian Huang , Heng Yu , Lidong Bing , Weihua Luo , Jiajun Chen

Language models (LMs) pre-trained on massive amounts of text, in particular bidirectional encoder representations from Transformers (BERT), generative pre-training (GPT), and GPT-2, have become a key technology for many natural language…

Computation and Language · Computer Science 2021-10-04 Xianrui Zheng , Chao Zhang , Philip C. Woodland

Distantly supervised relation extraction is widely used to extract relational facts from text, but suffers from noisy labels. Current relation extraction methods try to alleviate the noise by multi-instance learning and by providing…

Computation and Language · Computer Science 2019-06-21 Christoph Alt , Marc Hübner , Leonhard Hennig

We present the second version of the Open Assistant Toolkit (OAT-v2), an open-source task-oriented conversational system for composing generative neural models. OAT-v2 is a scalable and flexible assistant platform supporting multiple…

Information Retrieval · Computer Science 2024-03-04 Sophie Fischer , Federico Rossetto , Carlos Gemmell , Andrew Ramsay , Iain Mackie , Philip Zubel , Niklas Tecklenburg , Jeffrey Dalton

Esperanto is a widespread constructed language, known for its regular grammar and productive word formation. Besides having substantial resources available thanks to its online community, it remains relatively underexplored in the context…

Computation and Language · Computer Science 2026-04-01 Ona de Gibert , Lluís de Gibert

Despite significant advances in speech processing, Portuguese remains under-resourced due to the scarcity of public, large-scale, and high-quality datasets. To address this gap, we present a new dataset, named TAGARELA, composed of over…

Transformers have revolutionized machine learning, yet their inner workings remain opaque to many. We present Transformer Explainer, an interactive visualization tool designed for non-experts to learn about Transformers through the GPT-2…

Linguistic ambiguity continues to represent a significant challenge for natural language processing (NLP) systems, notwithstanding the advancements in architectures such as Transformers and BERT. Inspired by the recent success of…

Large Language Models (LLMs) represent a revolution in AI. However, they also pose many significant risks, such as the presence of biased, private, copyrighted or harmful text. For this reason we need open, transparent and safe solutions.…

Computation and Language · Computer Science 2023-10-24 Arno Candel , Jon McKinney , Philipp Singer , Pascal Pfeiffer , Maximilian Jeblick , Chun Ming Lee , Marcos V. Conde

In the last few years, three major topics received increased interest: deep learning, NLP and conversational agents. Bringing these three topics together to create an amazing digital customer experience and indeed deploy in production and…

Computation and Language · Computer Science 2021-07-27 Paulo Finardi , José Dié Viegas , Gustavo T. Ferreira , Alex F. Mansano , Vinicius F. Caridá

We present and make available pre-trained language models (Phraser, Word2Vec, Doc2Vec, FastText, and BERT) for the Brazilian legal language, a Python package with functions to facilitate their use, and a set of demonstrations/tutorials…

This paper presents an investigation of the capabilities of Generative Pre-trained Transformers (GPTs) to auto-generate graphical process models from multi-modal (i.e., text- and image-based) inputs. More precisely, we first introduce a…

Software Engineering · Computer Science 2024-06-10 Marvin Voelter , Raheleh Hadian , Timotheus Kampik , Marius Breitmayer , Manfred Reichert

ASR systems designed for native English (L1) usually underperform on non-native English (L2). To address this performance gap, \textbf{(i)} we extend our previous work to investigate fine-tuning of a pre-trained wav2vec 2.0 model…

Computation and Language · Computer Science 2022-02-11 Peter Sullivan , Toshiko Shibano , Muhammad Abdul-Mageed

Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to…

We introduce GPT-NeoX-20B, a 20 billion parameter autoregressive language model trained on the Pile, whose weights will be made freely and openly available to the public through a permissive license. It is, to the best of our knowledge, the…

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