activity
20232026
most citedAdvancing Neural Encoding of Portuguese with Transformer Albertina PT-*

36 citations · 49 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

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…

cs.CL2025

Hands-off Image Editing: Language-guided Editing without any Task-specific Labeling, Masking or even Training

Rodrigo Santos, António Branco, João Silva +1

Instruction-guided image editing consists in taking an image and an instruction and deliverring that image altered according to that instruction. State-of-the-art approaches to thi…

cs.CL2024

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*,…

cs.CL2024★ 5 cited

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…

cs.CL2024★ 6 cited

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…

cs.CL2024★ 2 cited

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…

cs.CL2024

Leveraging LLMs for On-the-Fly Instruction Guided Image Editing

Rodrigo Santos, João Silva, António Branco

The combination of language processing and image processing keeps attracting increased interest given recent impressive advances that leverage the combined strengths of both domain…

cs.CL2023★ 36 cited

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…