36 citations · 49 across the 8 of their papers we have counts for
8 papers
Progressing beyond Art Masterpieces or Touristic Clichés: how to assess your LLMs for cultural alignment?
António Branco, João Silva, Nuno Marques +10
Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- until recently there has been l…
CLARIN-PT-LDB: An Open LLM Leaderboard for Portuguese to assess Language, Culture and Civility
João Silva, Luís Gomes, António Branco
This paper reports on the development of a leaderboard of Open Large Language Models (LLM) for European Portuguese (PT-PT), and on its associated benchmarks. This leaderboard comes…
Sovereign AI-based Public Services are Viable and Affordable
António Branco, Luís Gomes, Rodrigo Santos +4
The rapid expansion of AI-based remote services has intensified debates about the long-term implications of growing structural concentration in infrastructure and expertise. As AI…
Open Sentence Embeddings for Portuguese with the Serafim PT* encoders family
Luís Gomes, António Branco, João Silva +2
Sentence encoder encode the semantics of their input, enabling key downstream applications such as classification, clustering, or retrieval. In this paper, we present Serafim PT*,…
PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese
Tomás Osório, Bernardo Leite, Henrique Lopes Cardoso +4
Leveraging research on the neural modelling of Portuguese, we contribute a collection of datasets for an array of language processing tasks and a corresponding collection of fine-t…
Fostering the Ecosystem of Open Neural Encoders for Portuguese with Albertina PT* Family
Rodrigo Santos, João Rodrigues, Luís Gomes +5
To foster the neural encoding of Portuguese, this paper contributes foundation encoder models that represent an expansion of the still very scarce ecosystem of large language model…
Advancing Generative AI for Portuguese with Open Decoder Gervásio PT*
Rodrigo Santos, João Silva, Luís Gomes +2
To advance the neural decoding of Portuguese, in this paper we present a fully open Transformer-based, instruction-tuned decoder model that sets a new state of the art in this resp…
Advancing Neural Encoding of Portuguese with Transformer Albertina PT-*
João Rodrigues, Luís Gomes, João Silva +4
To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation mo…