most citedIntroducing Bode: A Fine-Tuned Large Language Model for Portuguese Prompt-Based Task

7 citations · 12 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025★ 4 cited

Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge

Tobias Rueckert, David Rauber, Raphaela Maerkl +58

Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…

cs.CL2024★ 1 cited

A Review on Scientific Knowledge Extraction using Large Language Models in Biomedical Sciences

Gabriel Lino Garcia, João Renato Ribeiro Manesco, Pedro Henrique Paiola +3

The rapid advancement of large language models (LLMs) has opened new boundaries in the extraction and synthesis of medical knowledge, particularly within evidence synthesis. This p…

cs.CL2024

Adapting LLMs for the Medical Domain in Portuguese: A Study on Fine-Tuning and Model Evaluation

Pedro Henrique Paiola, Gabriel Lino Garcia, João Renato Ribeiro Manesco +3

This study evaluates the performance of large language models (LLMs) as medical agents in Portuguese, aiming to develop a reliable and relevant virtual assistant for healthcare pro…

cs.CL2024★ 7 cited

Introducing Bode: A Fine-Tuned Large Language Model for Portuguese Prompt-Based Task

Gabriel Lino Garcia, Pedro Henrique Paiola, Luis Henrique Morelli +7

Large Language Models (LLMs) are increasingly bringing advances to Natural Language Processing. However, low-resource languages, those lacking extensive prominence in datasets for…