6 citations · 13 across the 10 of their papers we have counts for
6 papers · 1 filter
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*,…
Meta-prompting Optimized Retrieval-augmented Generation
João Rodrigues, António Branco
Retrieval-augmented generation resorts to content retrieved from external sources in order to leverage the performance of large language models in downstream tasks. The excessive v…
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…
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…